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<br><br><ol><li><p>Design and implement scalable data platforms on <strong>Snowflake</strong> for retail analytics&nbsp;</p></li></ol><ol start="2"><li><p>Build and optimize ELT pipelines for retail data (POS, e-commerce, CRM, inventory, supply chain)&nbsp;</p></li></ol><ol start="3"><li><p>Leverage <strong>Snowflake Cortex</strong> to enable AI-driven use cases such as: Customer segmentation & personalization, Product recommendations, promo analysis&nbsp;</p></li></ol><ol start="4"><li><p>Integrate data from multiple retail systems (ERP, OMS, WMS, e-commerce platforms)&nbsp;</p></li></ol><ol start="5"><li><p>Develop data models for key retail metrics (sales, margins, inventory turnover, basket analysis)&nbsp;</p></li></ol><ol start="6"><li><p>Ensure data quality, governance, and compliance across datasets&nbsp;</p></li></ol><ol start="7"><li><p>Optimize Snowflake performance and cost for large-scale retail workloads&nbsp;</p></li></ol><ol start="8"><li><p>Collaborate with business stakeholders (merchandising, marketing, supply chain teams)&nbsp;</p></li></ol><ol start="9"><li><p>Enable near real-time analytics for inventory and order tracking&nbsp;</p></li></ol><br><p><strong>Desired Candidate Profile</strong></p><ol><li><p>5+ years of experience in Data Engineering, preferably in retail or e-commerce&nbsp;</p></li></ol><ol start="2"><li><p>Strong hands-on experience with Snowflake Data Cloud&nbsp;</p></li></ol><ol start="3"><li><p>Experience with Snowflake Cortex (AI/ML functions, LLM-powered analytics)&nbsp;</p></li></ol><ol start="4"><li><p>Advanced SQL and strong Python skills&nbsp;</p></li></ol><ol start="5"><li><p>Experience with ETL/ELT tools (dbt, Airflow, etc.)&nbsp;</p></li></ol><ol start="6"><li><p>Strong understanding of retail data models and KPIs&nbsp;</p></li></ol><ol start="7"><li><p>Experience with cloud platforms (AWS, Azure, or GCP)&nbsp;</p></li></ol><ol start="8"><li><p>Experience with BI tools (Tableau, Power BI, Looker)&nbsp;</p></li></ol><ol start="9"><li><p>Snowflake or cloud certifications (good to have)&nbsp;</p></li></ol>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We are looking for a detail-oriented Data Entry Operator to handle quotation preparation, billing, and invoicing for our trading operations.</p><ul><li><p>Prepare price quotations and generate sales invoices/billing documents</p></li><li><p>Enter and update customer orders, pricing, and product data in the ERP system</p></li><li><p>Maintain records of quotations, invoices, and purchase orders</p></li><li><p>Cross-check billing details (quantities, rates, taxes) for accuracy</p></li><li><p>Maintain product price lists and customer databases</p></li><li><p>Coordinate with sales, accounts, and warehouse teams on orders and reconciliation.</p></li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ol><li><p>Bachelor's degree/diploma in Commerce or related field</p></li><li><p>1–3 years' experience in data entry, billing, or quotations (trading/industrial preferred)</p></li><li><p>Proficient in MS Excel, Word, and ERP software (Tally, SAP, etc.)</p></li><li><p>Good typing speed, accuracy, and numerical skills</p></li><li><p>Strong attention to detail</p></li><li><p>Good English/Hindi communication skills</p></li></ol><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>Amazon is a deeply data-driven organization with an unwavering obsession for metrics and continuous improvement. As a Data Analyst, you will play a pivotal role in transforming complex datasets from multiple sources into meaningful, actionable reports that drive business outcomes. You will uncover root-cause insights, identify trends, and deliver data-driven recommendations that directly influence decision-making.<br>Working in close partnership with Learning &amp; Development teams, you will provide analytical expertise to support strategic initiatives, measure program effectiveness, and enable the business to operate with greater precision and impact.<br>Key job responsibilities<br>- Develop and maintain data collection processes and data management systems<br>- Design and execute SQL queries to compile, transform, and generate reports<br>- Create visualizations — charts, graphs, and dashboards (Tableau, QuickSight) — to support business decision-making and dive-deep activities<br>- Build automation solutions using Python to streamline recurring analyses<br>- Prepare and publish reports for business reviews (WBR, QBR, project updates)<br>- Partner with leadership to interpret data trends and provide actionable recommendations<br>- Conduct in-depth research into defect trends to identify root causes and improvement opportunities<br>- Perform data collection, entry, and mining as needed to support operational goals<br>- Translate complex analyses into clear, digestible standard reports<br>- Support Learning team projects with analytical expertise and data-driven insights<br>- Experience with written and verbal communication and presentation<br>- Experience using Microsoft Office (Excel, Word, PowerPoint, Outlook)<br>- Speak, write, and read fluently in English<br>Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.</p><br> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Nationality"> <b>Nationality</b> </div> <div class="col is-9 p5" data-automation-id="data_Nationality"> United Arab Emirates </div> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><span>The Data Protection Manager will support the Data Protection Officer (DPO) in delivering an effective data protection and privacy compliance framework across the ADGM. The role will help ensure that ADGM personal data is handled in accordance with applicable laws and regulatory expectations, while embedding a strong culture of accountability and responsible data use.</span></p><br><p><span>The role also includes responsibility for supporting the implementation and oversight of Artificial Intelligence (AI) governance.&nbsp;</span></p><br><p><span><strong>Data Protection and Privacy Compliance</strong></span></p><br><ul><li><span>Support the DPO in implementing and maintaining the organisation’s data protection framework&nbsp;</span></li><li><span>Provide day-to-day advice on data protection obligations to business units&nbsp;</span></li><li><span>Assist in identifying appropriate lawful bases for processing activities&nbsp;</span></li><li><span>Conduct and support Data Protection Impact Assessments (DPIAs)&nbsp;</span></li><li><span>Support with maintenance and updates of Records of Processing Activities (RoPA)&nbsp;</span></li><li><span>Draft and review privacy notices, policies, and procedures&nbsp;</span></li><li><span>Review and advise on data sharing agreements and processor contracts&nbsp;</span></li><li><span>Support responses to data subject rights requests (e.g. access, rectification, erasure)&nbsp;</span></li><li><span>Assist in managing and investigating personal data breaches, including root cause analysis and remediation&nbsp;</span></li><li><span>Monitor compliance with data protection laws and regulations and support internal audits and assurance activities&nbsp;</span></li><li><span>Deliver data protection training and awareness sessions to staff&nbsp;</span></li><li><span>Support cross-border data transfer assessments and safeguards&nbsp;</span></li><li><span>Assist with regulatory engagement and reporting obligations&nbsp;</span></li><li><span>Support development of data protection and AI governance metrics and reporting&nbsp;</span></li><li><span>Track and report on risks, issues, and remediation actions&nbsp;</span></li><li><span>Support continuous improvement of policies, controls, and processes&nbsp;</span></li><li><span>Promote a culture of data protection and responsible innovation across ADGM</span></li></ul><p><span><strong>Managerial&nbsp;</strong></span></p><br><ul><li><span>Creates an environment where team members consistently drive to improve performance</span></li><li><span>Manages team with full accountability for achieving overall agreed objectives</span></li><li><span>Manages by effectively empowering team members</span></li><li><span>Takes responsibility for mentoring high potential and most critical talent in their career progression</span></li><li><span>Reviews performance of team and addresses performance issues quickly through clear decisions</span></li></ul><p><span><strong>Information Security related</strong></span></p><br><ul><li><span>Understand, adopt, adhere and practice responsibilities or controls as per ADGM Information Security policy and as per best practices explained in the induction and awareness sessions.&nbsp;</span></li><li><span>Confidentiality, Integrity and availability of the ADGM Information shall be maintained at all times i.e. within as well as outside ADGM.&nbsp;</span></li></ul><p><span><strong>Education &amp; Work Experience:</strong></span></p><br><p><span>Bachelor’s degree in Law, Information Governance, Cybersecurity, or related field</span></p><br><p><span>Minimum 10 years of experience in a data protection, privacy, or similar role&nbsp;</span></p><br><p><span><strong>Essential</strong></span></p><br><ul><li><span>Relevant professional certification (e.g. CIPP/E, CIPM, or equivalent)</span></li></ul><p><span><strong>Desirable</strong></span></p><br><ul><li><span><strong>Experie</strong>nce within a regulatory, public sector, or highly regulated environment desirable</span></li><li><span>Exposure to AI, data analytics, or emerging technologies governance preferred</span></li></ul><p><span><strong>Required Competencies</strong></span></p><br><ul><li><span>Strong understanding of data protection laws and principles (e.g. UK GDPR or ADGM Data Protection Regulations 2021 or equivalent)&nbsp;</span></li><li><span>Understanding of AI governance principles, including fairness, accountability, transparency, and risk management&nbsp;</span></li><li><span>Experience conducting DPIAs or similar risk assessments&nbsp;</span></li><li><span>Ability to interpret legal and regulatory requirements and apply them pragmatically&nbsp;</span></li><li><span>Strong analytical and problem-solving skills&nbsp;</span></li><li><span>Excellent written and verbal communication skills&nbsp;</span></li><li><span>Ability to manage multiple priorities and stakeholders</span></li></ul><br>The ADGM Authority is mandated to facilitate the achievement of ADGM’s vision to be one of the world’s foremost international financial centers. The Authority brings together strategic and support functions to ensure the continued provision of best-in-class services, enabling the development of ADGM as a whole. It plays a pivotal role in driving ADGM’s growth by leveraging emerging trends across the international financial services sector and the developments associated with the post-pandemic world. </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><b>Position:</b> Data Entry Operator (Part-Time Home-Based Work)</p><p><b>Working Hours:</b> 02 to 03 hours per day</p><p><b>Income:</b> AED 2000 to AED 6,000</p><p><b>Education:</b> Any Degree</p><p><b>Location:</b> Work From Home (Remote)</p><p><br></p><p>We are seeking motivated, dedicated, and detail-oriented individuals to join our team as <b>Part-Time Data Entry Operators</b>. This is a flexible work-from-home opportunity for individuals who want to earn additional income while managing their own schedule.</p><p><br></p><p>Interested candidates may contact our HR Executive through the official contact below for job details and application guidance. Official Contact: [recruitmentatdataentry [at] gmail [•] com] (Replace (at) and (dot) with at and • when sending) Please mention your name and the phrase “Interested in Data Entry Job” in the email subject to receive full details.. Applications can be completed online or in person at the Dubai office.</p><p><br></p><p><b>Requirements:</b></p><ul><li>Laptop or Computer</li><li>Basic computer knowledge</li><li>Good typing speed</li><li>Internet connection</li></ul><p><b>Responsibilities:</b></p><ul><li>Enter data accurately and efficiently</li><li>Perform basic data entry and document processing tasks</li><li>Maintain confidentiality and security of all information</li><li>Complete assigned tasks within the given timefram</li></ul><p><br></p><p><b>Note:</b> This is not a network marketing or chain system.</p><p><br></p> </div><h2 class="h5">Skills</h2> <div data-jb-field="skills"><p>Data Entry</p><p>Typing Skills</p><p>Copy-Paste</p><p>Microsoft Word</p><p>Microsoft Excel</p><p>Computer Literacy</p><p>Attention to Detail</p><p>Data Accuracy</p></div>

Company Description<br>talabat is the leading on-demand food and non-food delivery platform in MENA, operating across 8 countries and processing hundreds of millions of orders annually. We're part of Delivery Hero, the global leader in online food delivery and q-commerce, and we're engineering-first. Our teams operate under<br>Data Governance Engineer As our data estate grows, we need someone to own governance across the organisation—ensuring data is secure, high-quality, discoverable, and compliant. You're not building pipelines or managing platforms—you're the person who defines what "secure" and "compliant" means, makes access policy calls independently, tests for it rigorously, and drives accountability when something breaks. You'll use AI tools—Claude, semantic layer generators, LLM-based data profilers—as your default to scale governance work while knowing when to stay human for policy decisions and escalations.<br>Your Profile:<br>You have extensive experience in data governance, data modelling, data quality, or compliance in regulated or fast-moving environments. You understand RBAC, access control models, data classification, and security best practices as lived experience, not certifications. You're genuinely fluent in SQL and data modeling; you can read and critique semantic layers (Look ML, Big Query). You can articulate trade-offs between strict access control and enabling velocity, and write findings documents that land with both technical and non-technical audiences.<br>You're AI-native—using Claude and semantic layer generators as part of your daily flow. You know which governance tasks scale through AI (auto-documentation, pattern detection, quality scoring) and which require human judgment (policy decisions, compliance interpretation, escalations). You can describe your workflow specifically: what you do by hand and what you delegate to AI.<br>What You'll Own:<br>Data Discovery:Build and maintain comprehensive data catalogs with machine-readable semantic layers that enable both humans and AI agents to understand and find accurate information Ensure every critical data asset has current, trustworthy documentation and is rapidly searchable Own the discovery outcome: comprehensively cataloged assets that teams can find without friction<br>Security & Access Control:Design and operate Role-Based Access Control frameworks that keep data appropriately segregated (by region, compliance zone, etc.) Monitor access requests, identify patterns, and make governance calls on standard requests independently Escalate complex conflicts but own most access decisions; prevent unauthorized access incidents entirely<br>Data Quality:Work with domain leaders (Finance, Operations, Product) to build reusable data quality frameworks and monitoring tools Establish global quality scores across freshness, consistency, and reliability Partner with teams to resolve underlying quality issues; ensure critical datasets fully meet quality standards<br>Compliance & Maturity:Align practices with international frameworks (DAMA/DMBOK, ISO standards) Perform regular maturity assessments across security, quality, and discoverability; work with teams to close gaps Maintain documented, verifiable compliance across all regulatory obligations<br>Stakeholder Alignment:Collaborate across business, engineering, and data science to standardize critical definitions (active users, revenue, customer segments) Embed these definitions into systems so reporting consistency is automatic, not manual Own the outcome: one source of truth for metrics across the organization<br>What Sets You Apart:<br>You speak multiple languages fluently: governance, data engineering, and business—constantly translating between them. You're comfortable making calls under ambiguity; when frameworks conflict or are incomplete, you decide what to do and own the outcome. You've shipped governance standards or compliance processes across teams. You think in systems—seeing how governance changes enable business velocity—and you optimize for it. You're adaptable: when governance standards evolve, you read them, evaluate applicability, operationalize what matters, and ignore what doesn't.<br>How You'll Progress:<br>Phase 1: Baseline & Foundation — Complete comprehensive audit of all data assets; define governance taxonomy with specific severity levels and pass/fail criteria; assess maturity against DAMA/DMBOK; build cross-functional relationships; establish decision-making framework and data access policy standard Phase 2: Operationalize & Automate — Deploy data catalog with critical assets documented and searchable; build RBAC framework with automated access review; create data quality frameworks for high-risk domains; define leakage standards; establish compliance reviews; implement AI-assisted documentation; significantly reduce approval time Phase 3: Scale Through Risk-Tiering — Implement risk-tiering logic (high/medium/low-risk assets get proportional scrutiny); deploy automated quality monitoring across critical datasets; scale catalog dramatically; build self-serve governance library; establish compliance dashboard; process access requests efficiently; shift team sentiment from blocker to enabler Phase 4: Embedded & Strategic — Achieve highly complete, searchable catalog with minimal search friction; risk-tiered governance is operating model; quality monitoring fully automated with most critical data meeting standards; self-serve library used comprehensively; compliance audits fully documented; make autonomous governance decisions at scale; use AI-assisted workflows to cut manual work significantly; influence how organization designs data with governance in mind; make independent policy decisions based on data; governance viewed as business enabler, not overhead

<ul><li><p>Designs and develops scalable machine learning models and AI-driven</p><p>solutions to address complex business challenges and enhance decision-</p><p>making processes</p><p>KEY RESPONSIBILITIE S</p><ul><li><p>Work with large and complex data sets to solve challenging business</p></li></ul><p>problems</p><ul><li><p>Collect, clean, and preprocess large datasets for analysis & model training</p></li><li><p>Perform exploratory data analysis (EDA) to uncover insights and inform model</p></li></ul><p>development</p><ul><li><p>Develop, train, and optimize machine learning models using state-of-the-art</p></li></ul><p>algorithms and frameworks</p><ul><li><p>Build end-to-end ML pipelines, including data ingestion, transformation, model</p></li></ul><p>training, validation, and deployment</p><ul><li><p>Automate workflows for model training, testing, and deployment using</p></li></ul><p>CI/CD pipelines and MLOps tools</p><ul><li><p>Collaborate with cross-functional teams to integrate models into applications</p></li></ul><p>and deliver end-to-end solutions</p></li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>5 years of experience in data science, machine learning, or AI</p><ul><li><p>Expertise in supervised/unsupervised learning, deep learning, NLP, computer</p></li></ul><p>vision, or generative AI (e.g., LLMs).</p><ul><li><p>Strong proficiency in Python and/or R; familiarity with SQL for data querying</p></li><li><p>Ability to build data pipelines (Spark, Airflow, Hadoop) and work with big data</p></li></ul><p>tools</p><ul><li><p>Understanding of model serving, API development (FastAPI, Flask), and</p></li></ul><p>optimizing model performance for real-time or batch inference.</p><ul><li><p>Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like</p></li></ul><p>MLflow/Kubeflow for model lifecycle management (MLOps)</p><p>Classified: Internal\ FAB.</p><p>Internal</p><ul><li><p>Experience deploying models on AWS, Google Cloud, Azure, or similar (e.g.,</p></li></ul><p>Sagemaker, Vertex AI)</p><ul><li><p>Educational qualifications: Master in Computer Science or a related field</p></li></ul><p>Work Experience</p><p>5-7Years</p></li></ul>

<ul><li><p>Work with large and complex data sets to solve challenging business problems</p></li><li><p>Collect, clean, and preprocess large datasets for analysis & model training</p></li><li><p>Perform exploratory data analysis (EDA) to uncover insights and inform model development</p></li><li><p>Develop, train, and optimize machine learning models using state-of-the-art algorithms and frameworks</p></li><li><p>Build end-to-end ML pipelines, including data ingestion, transformation, model training, validation, and deployment</p></li><li><p>Automate workflows for model training, testing, and deployment using CI/CD pipelines and MLOps tools</p></li><li><p>Collaborate with cross-functional teams to integrate models into applications and deliver end-to-end solutions</p></li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>5 years of experience in data science, machine learning, or AI</p></li><li><p>Expertise in supervised/unsupervised learning, deep learning, NLP, computer vision, or generative AI (e.g., LLMs).</p></li><li><p>Strong proficiency in Python and/or R; familiarity with SQL for data querying</p></li><li><p>Ability to build data pipelines (Spark, Airflow, Hadoop) and work with big data tools</p></li><li><p>Understanding of model serving, API development (FastAPI, Flask), and optimizing model performance for real-time or batch inference.</p></li><li><p>Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like MLflow/Kubeflow for model lifecycle management (MLOps)</p></li><li><p>Experience deploying models on AWS, Google Cloud, Azure, or similar (e.g., Sagemaker, Vertex AI)</p></li><li><p>Educational qualifications: Master in Computer Science or a related field.</p></li></ul><p>Skills</p><p>Machine Learning</p><p>Data Analysis</p><p>Python</p><p>Powered</p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>We are urgently looking for Data Entry Operators to join our remote team for part-time work.</p><p><br></p><p>Position Details:</p><p>* Job Type: Part-Time (Contract-Based)</p><p>* Location: Remote / Work from Home</p><p>* Working Hours: Only 2 to 3 hours per day</p><p>* Salary: AED 2,000 to AED 6,000 (Weekly &amp; Monthly Earnings)</p><p><br></p><p>Requirements:</p><p>* Basic computer knowledge</p><p>* Good typing speed and accuracy</p><p>* Laptop or computer with internet access</p><p>* Ability to maintain confidentiality</p><p>* Serious and responsible candidates only</p><p><br></p><p>Eligibility:</p><p>* Open to all nationalities</p><p>* Freshers and experienced candidates can apply</p><p>* Flexible timing available</p><p><br></p><p>Why Join Us?</p><p>* Easy online work</p><p>* Flexible schedule</p><p>* Work from the comfort of your home</p><p>* Training and support provided</p><p><br></p><p>Important Note:</p><p>This is a genuine job opportunity.</p><p>No network marketing. No chain system.</p> </div><h2 class="h5">Skills</h2> <div data-jb-field="skills"><p>Fast and accurate typing skills</p><p>* Basic computer knowledge</p><p>* Attention to detail</p><p>* Data entry accuracy</p><p>* Time management skills</p><p>* Ability to maintain confidentiality</p></div>

We are looking for Data Analytics trainees for our upcoming traineeship program.<br>Data Analytics Trainee Responsibilities:<br>Week 1 & 2: Training Modules – Candidates will be completing the learning modules assigned. Week 3: Live Project – Candidates will be working on the live project assigned to them by the company. Week 4: Project Report – Candidates will be preparing a project report and submit.<br>Data Analytics Trainee Requirements:<br>Bachelor’s degree or pursuing. Proficiency with computers, especially MS Office. High level of accountability and motivation. Strong Interpersonal, time and project management, presentation, leadership, and communication skills. Creativity and ability to delegate responsibilities. Receptiveness to feedback and adaptability. Willingness to meet deadlines.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><span><strong>Job Objective:</strong></span><span>To conduct statistical studies of cases, plan and organize data collection and analysis, design samples, and prepare the necessary analytical reports.</span><span>And to develop new processes for analyzing case data in line with achieving the Public Prosecution's strategic directions.</span></p><br><p><span><strong>Responsibilities:&nbsp;</strong></span></p><br><p><span>1. Planning and organizing the collection of case data, comparing it with approved performance indicators, and developing recommendations for improvement.</span></p><br><p><span>2. Preparing research, reports, and statistical studies related to case data and trends, and presenting them to relevant parties.</span></p><br><p><span>3. Conducting advanced analytical studies of case data, including an analysis of external influences, and submitting appropriate proposals and recommendations.</span></p><br><p><span>4. Analyzing data processing and collection processes, identifying opportunities for improvement, and advising data analysts.</span></p><br><p><span>5. Reviewing statistical analyses of cases, developing necessary recommendations in line with strategic objectives and performance indicators, and submitting them to decision-makers.</span></p><br><p><span>6. Providing members of the Public Prosecution with case data and statistics as required for monitoring and developing judicial work.</span></p><br><p><span>7. Preparing benchmarking studies and necessary research with leading entities at the local, regional, and international levels, identifying strengths and areas for improvement, preparing the necessary reports on the results, and submitting them to the direct supervisor, including recommendations and development proposals. 8. Submitting development proposals that contribute to improving judicial work based on the results of data analysis and study.</span></p><br> <p><span><strong>Academic qualification: </strong>Bachelor's degree in Business Analyst, preferably with a specialization in Statistics.</span></p><br><p><span><strong>Experience:&nbsp;</strong> 4 years of experience in the same field.</span></p><br><p><span><strong>National Service</strong>: Complete (Males only)</span></p><br><p><span>Gender: Male (only)</span></p><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><span>We are British Schools Overseas (BSO) accredited gaining Outstanding judgements in all standards, allowing us to offer the NQT, QTS and iPGCE programmes to our teachers through the TES Institute. GEMS Founders School, Abu Dhabi is truly unique and anyone who comes to work here has a wonderful opportunity to leave their mark. In line with our school vision, you will have the opportunity to Grow, Achieve and in everything you do at GFA</span></p> Skills <p>Successful candidates will need to:</p> <p><span><span>§<span>&nbsp; </span></span></span><span>The Data Lead needs to be a team player, service oriented and eager to learn;&nbsp;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>He/she need to have logical and analytical thinking skills and possess excellent ICT skills, including a good working knowledge of Microsoft Office;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>He/she must be excellent in communication skills – verbal and written; should be able to prioritise, effectively plan and have good organisational skills.</span></p> <p><b><span>Co-ordination within various departments:</span></b></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Co-ordinate with SENCo to ensure all SEN and IEP information is accurate and up to date;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Co-ordinate with the medical teams to ensure that all relevant medical data is available to all staff within a secure environment;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Co-ordinate and liaise with Examination Officer for internal examinations;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Co-ordinate with Operations department to support the student dispersal process;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Co-ordinate with the leader in charge of Data and Assessment to ensure the correct data collection procedures and reporting processes are in place on SIMS.</span></p> <p><b><span>Data input and management:</span></b></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Liaise with the Leaders responsible for the timetable, Heads of Year and Heads of Subject Areas to create class lists for the coming academic year;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Input data accurately and efficiently into Assessment Management systems, and transferring all school data from Microsoft Excel;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Write, design and produce reports illustrating general trends in school data.</span></p> <p><b><span>MIS updating:</span></b></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Input data where necessary into all of the MIS modules;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Adding Students and teachers onto the MIS system /set up new user accounts and logins.</span></p> <p><b><span>Staff and Parent Support:</span></b></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Production of class lists, medical, dietary and attendance reports and ensure they are updated on a regular basis.</span></p> <p><b><span>Impart Training;</span></b></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Deliver training to identify teaching and administrative staff within selected packages and with a particular focus on SIMS;</span></p> <p><span><span>§<span>&nbsp; </span></span></span><span>Deliver training on assessment data and how to record it.</span></p> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Years_of_experience"> <b>Years of experience</b> </div> <div class="col is-9 p5" data-automation-id="data_Years_of_experience"> No experience required </div> </div>

***HIRING***<br>Job Title – Data Scientist. Salary – AED 30,000 – AED 31,500 per month Contract Length – 6 Months (view to extend) Location – Abu Dhabi Start Date – ASAP<br>The customer is specifically looking for a Data Scientist (Not AI Engineer) with banking sector experience and strong hands-on exposure to credit risk-related projects, ideally with around 6 to 8 years of experience. This includes work on credit risk, loans, scoring platforms, scorecards, underwriting, or similar use cases. Strong data science depth is essential.<br>Role Overview<br>We are looking for a hands-on Senior Data Scientist with banking or financial services experience, particularly in credit risk and lending. The role involves developing machine learning solutions for loan underwriting, default prediction, and customer analytics, with ownership across model development, validation, deployment, and monitoring.<br>The ideal candidate should have strong technical fundamentals and be able to explain modelling decisions and business outcomes clearly.<br>Key Responsibilities Translate business requirements into modelling objectives, precise target definitions, and measurable success criteria. Develop models for credit scoring, loan underwriting, probability of default and borrower behavior analysis. Analyze credit bureau, transactional, repayment and behavioral data to improve risk assessment. Perform data preparation, feature engineering, and feature selection. Build and compare classification models using algorithms such as Random Forest, XGBoost, Light GBM and Cat Boost. Conduct hyperparameter tuning and apply appropriate validation methods, including cross validation and out of time testing. Evaluate model performance and select classification thresholds aligned with business priorities. Explain overall model behavior and individual customer predictions using techniques such as SHAP. Collaborate with engineering teams to deploy models and monitor performance, stability and data drift. Present model results, limitations and measurable business impact to technical and business stakeholders.<br>Required Skills and Experience Proven experience delivering machine learning projects, with clear ownership of technical decisions and outcomes. Banking or financial services experience, including hands on modelling for credit risk or lending. Understanding of loan products, underwriting, default definitions, repayment behavior, and credit bureau data. Strong proficiency in Python and SQL for data preparation, analysis, and modelling. Strong understanding of classification algorithms, bagging, boosting and the bias variance trade off. Practical knowledge of ROC AUC, KS, precision, recall, F1, confusion matrices and classification threshold selection. Experience with feature selection, correlation analysis, normalization, standardization, and model explainability. Strong understanding of data leakage, overfitting, underfitting, dataset splitting, and final model training. Ability to communicate technical concepts clearly and connect model performance to business KPIs.<br>Preferred Skills and Experience Experience with AWS and Amazon Sage Maker for model training, deployment, and monitoring. Experience with hyperparameter optimization tools such as Optuna. Experience developing customer propensity, recommendation, or cross selling models for financial products. Experience combining traditional credit data with alternative or behavioral data. Banking experience and hands-on AWS Sage Maker experience

<p>Data Processing Clerk</p> <p>A reputable company is seeking an organized Data Processing Clerk to manage records, update information, and support daily back-office operations. Freshers are welcome to apply.</p> <p>Responsibilities</p> <p>Enter and update data accurately in company systems<br /> Review documents and verify information<br /> Maintain digital and physical records<br /> Prepare basic reports and documentation<br /> Support daily administrative processing tasks</p> <p>Benefits</p> <p>Visa provided as per UAE Labor Law<br /> Medical insurance<br /> Career growth opportunities</p> <p>Location: Dubai, UAE<br /> Job Type: Full-Time</p> <p>Apply Now</p> <p>Email: hr.sinthia@gmail.com</p> <p>Only shortlisted candidates will be contacted.</p>

<p>Data Processing Clerk</p> <p>A reputable company is seeking an organized Data Processing Clerk to manage records, update information, and support daily back-office operations. Freshers are welcome to apply.</p> <p>Responsibilities</p> <p>Enter and update data accurately in company systems<br /> Review documents and verify information<br /> Maintain digital and physical records<br /> Prepare basic reports and documentation<br /> Support daily administrative processing tasks</p> <p>Benefits</p> <p>Visa provided as per UAE Labor Law<br /> Medical insurance<br /> Career growth opportunities</p> <p>Location: Dubai, UAE<br /> Job Type: Full-Time</p> <p>Apply Now</p> <p>Email: hr.sinthia@gmail.com</p> <p>Only shortlisted candidates will be contacted.</p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Company Description<br><p>Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.<br> &nbsp;</p><br><p>We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.<br> &nbsp;</p><br><p>Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.</p><br><br>Job Description<br><p>As the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.</p><br><p>As a <strong>Sr. Data Scientist (AI &amp; ML) on the global AI hub</strong>, your mission will be to design, build, and ship the machine learning and generative AI systems that power decisions across product and business. You will own a particular domain end to end, working closely with product and business managers as part of a talented team of data scientists and machine learning engineers. You will own the full ML lifecycle,&nbsp; from problem framing, data modeling, and feature engineering through model training, deployment, serving, and monitoring in production. Many of our initiatives will focus on leveraging Generative AI and LLMs for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations at scale.</p><br><p><strong>Responsibilities</strong></p><br><ul><li><p>Framing ambiguous business problems as well-defined machine learning and data science problems, with clear, objective success criteria.</p><br></li><li><p>Providing high-quality, impactful insights and data-driven recommendations through rigorous analysis and automated reporting to drive strategic organizational choices.</p><br></li><li><p>Designing, building, and shipping end-to-end machine learning and generative AI systems in production — spanning data pipelines, feature engineering, model training, serving, and monitoring.</p><br></li><li><p>Taking on engineering-heavy work end to end: architecting robust ML-based systems, writing clean and scalable production code, and training, deploying, and maintaining reliable ML models that solve real business problems at scale.</p><br></li><li><p>Training, evaluating, and iterating on models — selecting the simplest, most appropriate algorithms and architectures to deliver measurable business value.</p><br></li><li><p>Leveraging LLMs and generative AI for data enrichment, smart content understanding, and automated decision-making within production systems.</p><br></li><li><p>Building and maintaining the data models, features, and pipelines that power model training and allow us to measure performance and its drivers for your area of focus.</p><br></li><li><p>Designing, planning, and analyzing experiments (A/B and multivariate tests) to rigorously measure model and product impact.</p><br></li><li><p>Developing deep familiarity with source data and its generating systems through documentation, collaboration with engineering teams, and systematic data profiling.</p><br></li><li><p>Partnering with product and business teams to identify high-impact opportunities and translate them into ML solutions and actionable, data-driven recommendations.</p><br></li><li><p>Mentoring other data scientists in their growth journeys.</p><br></li><li><p>Elevating engineering and ML best practices — improving our ways of working, tooling, MLOps, and internal training programs.</p><br></li></ul><br>Qualifications<br><p><strong>Technical Experience</strong></p><br><ul><li><p>Deep expertise in machine learning, generative AI, deep learning, recommendation systems, NLP, pattern recognition, data mining.</p><br></li><li><p>Deep hands-on knowledge of ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Transformers, LLM fine-tuning).</p><br></li><li><p>Strong software engineering fundamentals: excellent coding skills, a solid grasp of data structures and algorithms, and proven ability in both general system design and ML system design.</p><br></li><li><p>Proven experience building, deploying, serving, and monitoring ML models in production, with a strong grasp of MLOps practices.</p><br></li><li><p>Strong data and ML engineering skills, including building and orchestrating data and training pipelines (e.g. via Airflow) and robust feature engineering.</p><br></li><li><p>Excellent SQL and competence with reproducible analysis and modeling in Python.</p><br></li><li><p>Solid statistical foundations, including experiment design and analysis (A/B and multivariate) and inferential, causal, and predictive methods.</p><br></li><li><p>Familiarity with data modeling and dimensional design.</p><br></li><li><p>Strong command over the entire ML lifecycle, from problem formulation and data auditing through modeling, deployment, interpretation, and presentation.</p><br></li><li><p>Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).</p><br></li><li><p>Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.</p><br></li><li><p>Familiarity with BigQuery and the Google Cloud Platform is a plus.</p><br></li></ul><p><strong>Qualifications</strong></p><br><ul><li><p>Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.</p><br></li><li><p>5+ years of experience across data science, machine learning engineering, and generative AI, including shipping ML models to production.</p><br></li><li><p>Experience building ML systems in an online consumer product setting is a plus.</p><br></li><li><p>A good problem solver with a 'figure it out' growth mindset.</p><br></li><li><p>An excellent collaborator.</p><br></li><li><p>An excellent communicator.</p><br></li><li><p>A strong sense of ownership and accountability.</p><br></li><li><p>A 'keep it simple' approach to #makeithappen.</p><br></li></ul><br><br> </div>

Experience: 2–5 years<br><br>Overview Supports the implementation of enterprise analytics transformation initiatives by developing data models, building BI reports, automating reporting processes, and assisting in AI-powered analytics projects. Responsibilities Semantic Model & Data Engineering Assist in building Bronze, Silver and Gold data layers. Develop and maintain data pipelines. Support data quality validation and reconciliation. Implement standardized business dimensions and shared keys. Maintain KPI documentation. Business Intelligence Build Power BI dashboards and reports. Develop recurring operational reports. Support month-over-month analysis. Assist with report automation. Automation Support automated report scheduling. Build simple workflows using Power Automate. Maintain reporting templates. AI & Agents Assist in configuring AI-powered reporting solutions. Support prompt development and testing. Help maintain reusable AI skills. Governance Perform data quality checks. Support audit documentation. Follow security and RLS standards<br>.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><b>osition: Part-Time Data Entry Operator (Remote Work From Home)</b></p><p><b>Working Hours:</b> 2 to 3 Hours Daily</p><p><b>Income:</b> AED 2,000 to AED 6,000 per Month</p><p><b>Education:</b> Any Degree</p><p><b>Work Location:</b> Remote / Home-Based</p><p>We are looking for reliable, self-motivated, and detail-oriented candidates to join our team as <b>Part-Time Data Entry Operators</b>. This is a flexible remote work opportunity suitable for students, homemakers, freelancers, and individuals looking for an additional source of income while working from the comfort of their home.</p><p><br></p><p>Interested candidates may contact our HR Executive through the official contact below for job details and application guidance. Contact: [recruitmentatdataentry {at} gmail {•} com] (Replace (at) and (dot) with at and • when sending)</p><p><br></p><p><b>Requirements:</b></p><ul><li>Laptop or Computer</li><li>Basic computer knowledge</li><li>Good typing speed and accuracy</li><li>Stable internet connection</li><li>Ability to follow instructions and complete tasks on time</li></ul><p><b>Job Responsibilities:</b></p><ul><li>Enter and update data accurately in assigned systems</li><li>Perform basic data entry and document processing tasks</li><li>Review information for accuracy and maintain quality standards</li><li>Handle company information with confidentiality</li><li>Complete assigned projects within the given deadlines</li></ul><p><br></p> </div><h2 class="h5">Skills</h2> <div data-jb-field="skills"><p>Data Entry Skills</p><p>Typing Speed and Accuracy</p><p>Copy-Paste Skills</p><p>Microsoft Word &amp; Excel Knowledge</p><p>Basic Computer Skills</p><p>Data Accuracy and Attention to Detail</p><p>Document Processing Skills</p></div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><b>Position: Part-Time Data Entry Operator (Remote Work From Home)</b></p><p><b>Working Hours:</b> 2 to 3 Hours Daily</p><p><b>Salary Range:</b> AED 2,000 – AED 6,000 per week and Month</p><p><b>Education:</b> Any Degree</p><p><b>Work Location:</b> Remote / Home-Based</p><p>We are looking for reliable, self-motivated, and detail-oriented candidates to join our team as <b>Part-Time Data Entry Operators</b>. This is a flexible remote work opportunity suitable for students, homemakers, freelancers, and individuals looking for an additional source of income while working from the comfort of their home.</p><p><br></p><p>Interested candidates may contact our HR Executive through the official contact below for job details and application guidance. Official Contact: [recruitmentatdataentry {at} gmail {•} com] (Replace (at) and (dot) with at and • when sending) Please mention your name and the phrase “Interested in Data Entry Job” in the email subject to receive full details.. Applications can be completed online or in person at the Dubai office.</p><p><b>Requirements:</b></p><ul><li>Laptop or Computer</li><li>Basic computer knowledge</li><li>Good typing speed and accuracy</li><li>Stable internet connection</li><li>Ability to follow instructions and complete tasks on time</li></ul><p><b>Job Responsibilities:</b></p><ul><li>Enter and update data accurately in assigned systems</li><li>Perform basic data entry and document processing tasks</li><li>Review information for accuracy and maintain quality standards</li><li>Handle company information with confidentiality</li><li>Complete assigned projects within the given deadlines</li></ul><p><b>Important Note:</b></p><p>This is a genuine data entry opportunity. It is <b>not related to network marketing, MLM, or any chain referral system.</b></p> </div><h2 class="h5">Skills</h2> <div data-jb-field="skills"><p>Data Entry</p><p>Typing Skills</p><p>Copy-Paste Operations</p><p>Microsoft Word</p><p>Microsoft Excel</p><p>Computer Literacy</p></div>

About the Role Neo Stats is hiring experienced Data Scientists to work on advanced analytics and machine learning engagements for leading retail banking clients in the UAE. We are looking for candidates with strong experience in either Marketing Analytics or Credit Analytics within Retail Banking. Experience across both areas will be an added advantage. This is a hands-on Data Science role focused on building, optimizing, validating and implementing machine learning models that directly support customer growth, credit decisioning, risk management and portfolio performance. Retail Banking experience is mandatory.<br>Key Responsibilities Build, validate, optimize and monitor machine learning models for retail banking use cases. Develop Marketing Analytics solutions including customer segmentation, propensity modelling, churn prediction, campaign targeting, cross-sell, upsell, next-best-action and customer lifetime value. Develop Credit Analytics solutions including application scoring, behavioral scoring, risk segmentation, early warning indicators, collections prioritization and portfolio risk analysis. Perform data exploration, feature engineering, model selection, hyperparameter tuning and model validation. Work with customer, transaction, product, campaign, bureau and credit performance data. Translate banking business requirements into practical Data Science and Machine Learning solutions. Collaborate with business, risk, marketing, technology and data engineering teams. Present model findings and recommendations to client stakeholders. Support model governance, documentation, validation and ongoing performance monitoring.<br>Required Skills & Experience5+ years of hands-on Data Science experience. Mandatory experience in Retail Banking Analytics. Strong experience in Marketing Analytics, Credit Analytics, or both. Proven hands-on experience building and optimizing Machine Learning models. Strong programming skills in Python and SQL. Experience working with large and complex banking datasets. Strong understanding of statistical modelling, feature engineering and model evaluation. Strong analytical and problem-solving skills. Good client-facing and stakeholder-management capabilities. Willingness to work from the client location in the UAE.<br>Preferred Skills Experience with Databricks, Dataiku, Azure or similar platforms. Exposure to MLOps, model deployment and model monitoring. Experience in campaign optimization, customer value management, collections analytics or portfolio risk management. Bachelor's or master's degree in data science, Statistics, Mathematics, Computer Science, Engineering, Economics or a related quantitative discipline.<br>Candidate Eligibility Candidates currently based in UAE or India may apply. Candidates based in India should be willing to relocate to the UAE and work from the client location. Only candidates who can join immediately or within 30 days should apply.