Lead Data Scientist - Banking

• Strong knowledge of statistics, machine learning fundamentals, similarity matching, classification, clustering, and model evaluation.
• Hands-on experience in customer data modelling, identity resolution, deduplication, segmentation, and data quality analysis.
• Proficient in Python for data exploration, transformation, model prototyping, and analytical validation.
• Strong SQL skills for data investigation, profiling, and validation.
• Familiarity with Microsoft Fabric, notebooks, and lakehouse concepts for analytical processing.
• Ability to design and validate data-driven models for anomaly detection, matching optimization, and scoring.
• Experience working with cross-functional teams including product, data, and engineering teams.

Additional

Skills (Added Advantage)

• Experience with Dataverse, Dynamics 365 Sales / Customer Service / CI Journeys /similar Customer Data Platforms.
• Exposure to Azure ecosystem (Fabric, Synapse, ADLS, Power BI).
• Knowledge of feature engineering, experimentation, and model performance tuning.
• Understanding of data governance, privacy, and responsible • Experience with customer segmentation analytics, propensity modeling, or scoring techniques.