Data Scientist

What You Will Do

• Analyze customer, transactional, behavioral, and product data to identify trends and business opportunities.
• Perform exploratory data analysis (EDA) and generate actionable insights.
• Develop dashboards and reports to support business decision making.
• Translate business problems into analytical solutions.

Machine Learning and AI Development

• Build, validate, and deploy machine learning models for:
• Propensity Modeling
• Customer Segmentation
• Churn Prediction
• Next Best Action (NBA)
• Cross-Sell/Upsell Recommendations
• Fraud Detection
• Credit Risk Modeling
• Collections & Recovery Analytics
• Apply statistical and machine learning techniques to solve business problems.
• Monitor model performance and recommend enhancements.

Data Preparation and Engineering

• Extract, cleanse, transform, and integrate data from multiple sources.
• Create reusable feature engineering pipelines.
• Ensure data quality, consistency, and governance standards are maintained.
• Work closely with Data Engineering teams on data sourcing and pipeline development.

Model Governance

• Prepare model development documentation and validation packs.
• Support model governance requirements and regulatory compliance.
• Maintain model inventories and monitoring reports.
• Assist during internal audit and model validation exercises.

Stakeholder Management

• Collaborate with business teams to understand requirements.
• Present analytical findings in a clear and business-friendly manner.
• Participate in project discussions and workshops.

Innovation and Research

• Continuously evaluate emerging AI/ML techniques.
• Conduct Proof of Concepts (PoCs) for new use cases.
• Identify opportunities for automation and advanced analytics adoption.