Data Scientist Credit Risk & Machine Learning (FINTECH) (Pune Division)

Job Description

Data Scientist Credit Risk & Machine Learning (FINTECH) Pune, India Immediate Joiners Preferred Mandatory: Prior FINTECH experience in credit scoring, digital lending, and fraud management. We are partnering with a leading FINTECH organisation to hire an experienced Data Scientist who will play a pivotal role in building and optimising data-driven lending solutions. This opportunity is ideal for professionals with deep expertise in credit risk analytics, money lending products, and fraud detection , who are passionate about using machine learning to drive business impact. Key Responsibilities Develop, enhance, and maintain credit risk and credit scoring models using advanced statistical and machine learning techniques. Collaborate with third-party partners and data providers on credit scoring initiatives, model evaluation, and portfolio performance analysis. Build predictive models for: Credit risk assessment Fraud detection and fraud management Lending portfolio optimisation Other high-impact business use cases. Analyse large and complex datasets to identify trends, opportunities, and risks that improve lending decisions. Monitor, validate, and continuously improve model performance and effectiveness. Work closely with Data Engineering and Software Engineering teams to develop scalable, production-ready solutions. Create dashboards and reports that translate data insights into actionable recommendations for business stakeholders. Stay updated on emerging trends, technologies, and regulatory developments within Data Science and Credit Risk. Mentor junior Data Scientists and contribute to capability building within the team. Support the Head of Data in driving the organisations data strategy. What Were Looking For - Mandatory Requirements: Masters degree in Computer Science, Statistics, Mathematics, Economics, or a related quantitative discipline. 2 - 3 years of experience in Data Science. Mandatory FINTECH experience involving: Credit Scoring Digital/Money Lending Products Fraud Detection and Fraud Management Proven experience developing and deploying credit risk models within a FINTECH workplace. Strong understanding of credit risk frameworks, regulations, and industry best practices. Strong programming skills in Python and SQL (R is an added advantage). Hands-on experience with model deployment, model monitoring, CI/CD practices, databases, and scalable systems design. Expertise in machine learning and statistical techniques, including: Logistic Regression Decision Trees Random Forests Gradient Boosting Machines Neural Networks. Ability to translate business objectives into practical, data-driven solutions. Excellent communication and stakeholder management skills. Proven ability to work effectively with third parties and cross-functional teams. Preferred Experience mentoring junior Data Scientists. GitHub projects, open-source contributions, or published research. Experience working in fast-paced, product-led environments. Who You Are Practical, hardworking, and hands-on. Results-oriented with strong business acumen. Analytical and proactive in solving problems. Able to manage multiple priorities and thrive in dynamic environments. Passionate about building scalable solutions that deliver measurable business outcomes. Immediate Joiners Preferred If you have a strong FINTECH background with expertise in credit scoring, lending, and fraud management , and are available to join immediately or within a short notice period, wed love to hear from you. Apply with your updated CV and GitHub profile (if applicable). Data Scientist Credit Risk & Machine Learning (FINTECH) Pune, India Immediate Joiners Preferred Mandatory: Prior FINTECH experience in credit scoring, digital lending, and fraud management. We are partnering with a leading FINTECH organisation to hire an experienced Data Scientist who will play a pivotal role in building and optimising data-driven lending solutions. This opportunity is ideal for professionals with deep expertise in credit risk analytics, money lending products, and fraud detection , who are passionate about using machine learning to drive business impact. Key Responsibilities Develop, enhance, and maintain credit risk and credit scoring models using advanced statistical and machine learning techniques. Collaborate with third-party partners and data providers on credit scoring initiatives, model evaluation, and portfolio performance analysis. Build predictive models for: Credit risk assessment Fraud detection and fraud management Lending portfolio optimisation Other high-impact business use cases. Analyse large and complex datasets to identify trends, opportunities, and risks that improve lending decisions. Monitor, validate, and continuously improve model performance and effectiveness. Work closely with Data Engineering and Software Engineering teams to develop scalable, production-ready solutions. Create dashboards and reports that translate data insights into actionable

Keyskills :
Data ScienceCredit Risk AnalyticsMachine LearningPythonSQLLogistic RegressionDecision TreesNeural NetworksStakeholder ManagementRandom Forests