Data Scientist -Fintech
MUTHOOT PAPPACHAN TECHNOLOGIES LTD - Technopark (confirm workplace)
Apply by 2026-10-31
About the role
Experience: 5+ Years Industry Preference: FinTech / Banking / NBFC / Lending Role Overview We are looking for an experienced Data Scientist with strong analytical capabilities and hands-on experience in building, deploying, and maintaining machine learning models in a FinTech environment. The role requires translating business problems into data-driven solutions , particularly in areas such as customer propensity modelling, risk analytics, and customer behaviour analysis . The candidate should be comfortable working with large datasets, collaborating with business teams, and operationalizing models in production environments. Key Responsibilities 1. Data Analysis & Business Insights Analyse large structured and semi-structured datasets to generate business insights for financial products and customer behaviour . Translate business problems into analytical frameworks and data science solutions . Perform exploratory data analysis to identify trends, patterns, and opportunities for product growth. 2. Machine Learning Model Development Design, develop, and validate machine learning models for use cases such as: Customer propensity models Cross-sell / up-sell prediction Customer segmentation Risk or fraud-related analytics Apply statistical and machine learning techniques such as logistic regression, tree-based models, boosting algorithms, and clustering . 3. Model Deployment & Lifecycle Management Deploy ML models into production environments. Build pipelines for model monitoring, retraining, and performance tracking . Maintain and optimize existing models to ensure accuracy and stability. 4. Collaboration with Business & Product Teams Work closely with product, risk, marketing, and business teams to understand requirements. Convert analytical outputs into actionable recommendations . Support decision-making through data-driven insights and dashboards . 5. Advanced Analytics & AI (Good to Have) Knowledge or hands-on exposure to Large Language Models (LLMs) and Generative AI. Experience in LLM-powered analytics assistants, RAG pipelines, or conversational data interfaces is an advantage. Required Skills Technical Skills Strong programming skills in Python or R . Solid knowledge of SQL and working with large datasets. Experience with machine learning frameworks such as Scikit-learn, XGBoost, or similar. Experience in feature engineering, model evaluation, and hyperparameter tuning . Experience deploying models using APIs, batch pipelines, or ML platforms . Analytics Skills Strong foundation in statistics and predictive modelling . Experience in propensity modelling and customer behaviour analytics . Ability to translate business problems into analytical solutions . Data Tools Experience with cloud platforms (AWS/GCP/Azure) is preferred. Familiarity with data visualization tools (Power BI, QuickSight, Tableau) is a plus. Preferred Skills Domain Experience Prior experience in FinTech, Banking, Lending, NBFC, or Financial Services . Understanding of customer lifecycle, lending products, credit analytics, or cross-sell strategies .
Requirements
- Domain Experience
- Prior experience in
- FinTech
- Banking
- Lending
- NBFC
- or Financial Services
- .
- Understanding of
- customer lifecycle
- lending products
- credit analytics
- or cross-sell strategies
- .