Data Scientist

Position: Data Scientist
Location: Mumbai, Maharashtra
Experience: 2–5 years

About the Role:
We are looking for a skilled Data Scientist to join our fast-growing fintech NBFC. In this role, you’ll help shape the organization’s data strategy, build predictive models, and generate insights that enhance credit risk management, operational efficiency, and customer experience. You’ll work closely with product, business, and engineering teams to create scalable, data-driven solutions that influence key strategic decisions.

Key Responsibilities:

• Develop and implement predictive models for credit scoring, fraud detection, and portfolio risk segmentation using machine learning and statistical methods.

• Analyze customer and business data to identify trends and generate actionable insights for product design, underwriting, and collections.

• Collaborate with cross-functional teams to design data experiments and evaluate their outcomes using A/B testing and key performance metrics.

• Build automated data pipelines, feature repositories, and real-time dashboards to support faster decision-making.

• Work with engineering teams to deploy and maintain models in production environments.

• Conduct exploratory data analysis (EDA) to uncover patterns and inform lending strategies.

• Continuously refine and monitor model performance to ensure accuracy, interpretability, and compliance.

• Contribute to the establishment of robust MLOps and data governance frameworks for scalable deployments.

• Stay abreast of new tools, algorithms, and best practices in data science and financial technology.

Qualifications:

• Experience: 2–5 years in data science, machine learning, or advanced analytics (experience in fintech or BFSI preferred).

• Technical Skills:

  • Proficiency in Python (pandas, scikit-learn, NumPy, etc.).

  • Experience with SQL/MySQL and visualization platforms (Tableau, Power BI, Superset, or similar).

  • Understanding of statistical modeling, regression, classification, clustering, and time-series forecasting.

  • Familiarity with model lifecycle management and MLOps workflows.

• Education: Bachelor’s or Master’s degree in Engineering, Statistics, Mathematics, Economics, or another quantitative discipline.

• Strong analytical and communication skills with the ability to simplify complex findings for business stakeholders.

• Passion for solving financial inclusion and lending-related challenges using data.

• A proactive, self-driven approach suited to a fast-paced, high-growth environment.