Job Description

Roles & Responsibilities

1. Data Analysis & Insight Generation

Analyze large datasets to identify trends and generate actionable insights for decision making and operational efficiency.

Communicate findings through visualizations and clear storytelling.

1. Machine Learning & Model Development

Develop and deploy machine learning models for use cases such as forecasting, optimization, and risk analysis.

Apply statistical and machine learning techniques to solve complex business problems.

1. Data Preparation & Feature Engineering

Prepare data through extraction, cleaning, preprocessing, and feature engineering.

Ensure data quality and integrity for reliable model performance.

1. Model Deployment & Monitoring

Deploy models into production and monitor performance for drift or degradation.

Continuously improve models based on feedback and new data.

1. Collaboration & Stakeholder Engagement

Work with business teams to translate requirements into analytical solutions.

Collaborate with Data Engineering and Data Governance teams for end to end delivery.

1. AI Governance

Ensure all AI and machine learning activities comply with governance, privacy, and regulatory requirements by following defined lifecycle processes, risk classification, and using approved governed data.

Implement responsible and secure AI practices, including bias and fairness checks, explainability, model documentation, auditability, and collaboration with Cybersecurity and Data Governance teams.

Desired Candidate Profile

• Minimum Qualifications

  • Bachelor's or Master's Degree in Data Science, Artificial Intelligence (AI), Statistics, Computer Science, or a related field.

  Minimum Experience

  • Minimum 5+ years of experience in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics.

  • Proven experience developing, deploying, and maintaining machine learning models in production environments.

  • Experience working with large-scale datasets and cloud-based analytics platforms is preferred.

  Skills & Competencies

  • Strong programming skills in Python (preferred) or R.

  • Experience with large-scale data processing using SQL, Spark, or similar technologies.

  • Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.

  • Experience in end-to-end machine learning model development, validation, deployment, and optimization.

  • Knowledge of MLOps practices, including CI/CD pipelines, model monitoring, version control, and automated retraining.

  • Understanding of data engineering concepts, data pipelines, and cloud data platforms, preferably Microsoft Azure and Databricks.

  • Strong knowledge of statistical analysis, predictive modeling, feature engineering, and data preprocessing techniques.

  • Experience using data visualization tools such as Power BI and Tableau to communicate analytical insights.

  • Understanding of data governance, data quality management, privacy regulations, and AI governance principles.

  • Strong analytical thinking, problem-solving, and critical reasoning skills.

  • Excellent communication, presentation, and stakeholder management skills.

  • Ability to work collaboratively with cross-functional teams in an agile environment.

  • Strong organizational skills with the ability to manage multiple priorities and deliver high-quality outcomes within deadlines.