Data Scientist

Job Description For specific focus areas it is listed below (Your skillset should be aligned with at least one focus area).

Key responsibilities of the data scientist would be:

Collection Insights & Analytics:

Build real-time business performance dashboards for risk monitoring

0 to 2 years of experience with Power BI and SQL as a data analyst or similar role.

Strong analytical mindset with attention to data accuracy and problem solving, and an ability to work independently.

Strong background in writing advanced SQL queries (joins, filters, window functions, etc.).

Experienced at building Power BI data models and manage relationships between multiple tables. Comfortable using DAX for building complex measures, calculated columns, Parameters etc.

Ability to troubleshoot and debug issues when reports or data pipelines break.

Effective communication skills to translate business needs into analytical solutions.

Experienced in working with large datasets from different sources.

Basic knowledge of Python for data wrangling (numpy, pandas)

Model Development & Scorecard Creation:

Design risk assessment scorecards for all lending stages (pre-acquisition to recoveries) using explainable ML techniques

Develop proprietary variables from mainstream (credit bureau, application data) and alternative sources (social media, transaction patterns)

Implement supervised/unsupervised learning models combining structured and unstructured data

Convert raw data (bureau, transactional, social media) into actionable features via techniques like dimensionality reduction, interaction terms, and temporal aggregation

Data Infrastructure & Analytics:

Build real-time business performance dashboards for risk monitoring

Maintain a continuously-updating Business Rule Engine that codifies lending policies using Python

Optimize Python-based feature pipelines for GPU acceleration (CUDA/Numba) and Spark/Dask distributed processing

Establish data handling protocols for extraction, cleaning, and pipeline maintenance