Experience
2 - 4 yrs
Salary (CTC)
₹15.8L - ₹23L
Job Location
Gurugram, India
Vacancy
1
Designation
Data Scientist
Job Type
Not specified
Job Description
Credit Scoring & Risk Models: Build and refine credit scoring models using statistical and machine learning techniques tailored for fintech and NBFC use cases.
Data Analytics & Insights: Analyze structured and unstructured datasets to uncover patterns, trends, and insights that drive better decision-making.
Model Development & Testing: Develop predictive models for risk assessment,customer segmentation, and product optimization; perform validation and back-testing to ensure accuracy.
Experimentation: Support A/B testing and other controlled experiments to measure product impact and improve business strategies.
Visualization & Reporting: Create dashboards and reports to present model results and business insights to non-technical stakeholders.
Data Preparation: Collect, clean, and preprocess raw data for modeling and analysis, ensuring high data quality and consistency.
Collaboration: Work closely with product managers, engineers, and business teams to define problems, develop solutions, and integrate models into business workflows.
Model Deployment Support: Assist in deploying machine learning models into production environments and monitoring their performance.
Who You Are:
Experience: 2 4 years of experience in Data Science, preferably in the fintech/NBFC/banking domain.
Credit Scoring Expertise: Hands-on experience in developing and implementing credit risk/credit scoring models.
Technical Skills: Proficiency in Python, SQL, and Excel for data manipulation, analysis, and modeling.
Cloud & Tools: Exposure to AWS (or other cloud platforms) and Git for version control.
Statistical Knowledge: Strong grasp of regression, decision trees, clustering,hypothesis testing, and other ML/statistical techniques.
Visualization: Ability to present findings using tools like Tableau, Power BI, or visualization libraries (matplotlib, seaborn, plotly).
Problem-Solver: Strong analytical thinking and ability to translate business requirements into data-driven solutions.
Communication: Comfortable explaining technical concepts and model outcomes to business and product stakeholders.
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