Data Science for Decision Engine

Key Responsibilities

Model Development & Deployment

• Develop and maintain credit risk assessment and lending decisions modules

• Expertise for handling large financial databases and credit data manipulation

• Design and implement credit-risk decisioning model solutions using API-based frameworks (e.g., Flask, FastAPI) or event-driven architecture (e.g., Kafka, Pub/Sub), along with other suitable technologies

• Monitor model performance to ensure high accuracy and reliability in credit decisions

Data Analysis & Risk Assessment

• Clean and preprocess financial datasets, particularly credit lending and risk data

• Conduct advanced statistical analyses to support risk assessment and lending decisions

Required Qualifications

Technical Skills

• Proficiency in Python, SQL, and machine learning libraries (TensorFlow, PyTorch, Scikit-Learn)

• Experience with cloud platforms (AWS,GCP) for model deployment

• Knowledge of statistical and machine learning techniques for risk modeling

Domain Expertise

• Understanding of credit lending and risk assessment principles

• Experience in financial data analysis within regulatory constraints

• Proven track record in developing credit decision engines (optional)

Education & Experience

• Bachelor’s degree or higher in Statistics, Computer Science, Mathematics, or related field

• Minimum 3 years experience in retail lending or similar role

Additional Requirements

• Strong communication skills for presenting complex findings and process flow to management

• Experience with data visualization tools (Tableau, Power BI)

• Ability to work collaboratively with cross-functional teams