Data Scientist

About the Company

SaveIN is a Y-Combinator-backed, fast-growing healthcare technology company revolutionizing healthcare access in India. Based in Gurugram, we are proudly backed by YC and top investors from the US and Europe. Our innovative products span healthcare aggregation, payments, finance, and SaaS, making healthcare more accessible and affordable.Tips: Provide a summary of the role, what success in the position looks like, and how this role fits into the organization overall.

About the Role

We are looking for a Data Scientist to join our Data Science & Risk team. This role offers an opportunity to work on large-scale financial datasets, including credit bureau data and alternate data sources, to design and enhance underwriting models, portfolio monitoring frameworks, and customer risk strategies. The position provides hands-on exposure to machine learning applications in credit risk, collections, and customer lifecycle management.

Key Responsibilities

• Contribute to the development, validation, and deployment of ML models for credit underwriting, collections, and portfolio risk monitoring.
• Perform advanced feature engineering using bureau, transaction, and alternate datasets to improve predictive power.
• Build and maintain reporting dashboards (e.g., PowerBI) to provide actionable insights for risk and business stakeholders.
• Automate recurring data workflows and scoring pipelines to improve scalability and reduce manual effort.
• Conduct exploratory data analysis and statistical deep-dives to uncover customer behavior patterns and portfolio trends.
• Collaborate with cross-functional teams (Product, Operations, Risk) to translate business requirements into data-driven solutions.
• Document methodologies, experiments, and findings to ensure reproducibility and knowledge sharing.
• Ensure data quality through validation, cleansing, and monitoring processes.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or related field.
• 0–2 years of relevant experience in data science, machine learning, or analytics.
• Strong programming skills in Python (pandas, numpy, scikit-learn, etc.) and SQL.
• Solid understanding of machine learning algorithms (classification, regression, ensemble methods).
• Knowledge of credit bureau data (CIBIL, CRIF, Experian, etc.) and alternate data sources is a strong plus.
• Familiarity with risk modeling, scorecards, or credit decision systems preferred.
• Experience with visualization tools (PowerBI/Tableau) and version control (Git).
• Exposure to cloud platforms (AWS/GCP/Azure) is desirable.
• Exposure to distributed data systems (e.g., Spark, Hadoop, BigQuery) is a plus.
• Strong analytical thinking, communication skills, and ability to thrive in a fast-paced fintech environment.

Key Competencies

• Excellent problem-solving, quantitative, and analytical skills.
• Strong attention to detail and commitment to data quality.
• Ability to present complex technical insights in a clear, structured, and business-friendly format.
• Creativity, innovation, and self-motivation with a sense of urgency.
• Ability to work under ambiguity and prioritize multiple tasks effectively.
• Strong team player with excellent communication and collaboration skills.
• Ability to manage projects end-to-end and align with stakeholders on requirements and outcomes.

What We Offer

• End-to-end exposure to production-grade ML model development in credit risk and fintech.
• Opportunity to work closely with senior data scientists and business stakeholders on high-impact projects.
• A collaborative and innovative environment where data drives decision-making.
• Competitive compensation and benefits.

If you’re passionate about applying data science in fintech and eager to build impactful risk models, we’d love to hear from you.