Data Scientist

FinBox

Gurgaon, Haryana
Permanent
Full-time

7 days ago

FinBox: Where Fintech Meets Fun!Welcome to FinBox, the buzzing hive of tech innovation and creativity!Since our inception in 2017, FinBox has built some of the most advanced technologies in the financial services space that help lenders like Banks, NBFCs and large enterprises build and launch credit products within a matter of days, not months or years. FinBox is a Series A funded company which is expanding globally with offices in India, Vietnam, Indonesia and Philippines.Our vision is to build the best-in-class infrastructure for lending products and help Banks & Financial Services companies across the world scale and launch credit programs that set a new standard in the era of digital finance. So far, we’ve helped our customers disburse Billions of Dollars in credit across unsecured and secured credit including personal loans, working capital loans, business loans, mortgage and education loans. FinBox solutions are already being used by over 100+ companies to deliver credit to over 5 million customers every month.Why Should You be a FinBoxer:

Innovative Environment: At FinBox, we foster a culture of creativity and experimentation, encouraging our team to push the boundaries of what's possible in fintech.
Impactful Work: Your contributions will directly impact the lives of millions, helping to provide fair and accessible credit to individuals and businesses alike.
Growth Opportunities: We are a Series A funded startup and have ample opportunities for growth, professional development and career advancement.
Collaborative Culture: Join a diverse and inclusive team of experts who are passionate about making a difference and supporting one another.

Who’s a Great FinBoxer:At FinBox, we’re on the lookout for exceptional folks who are all about innovation and impact. If you’re excited to shake things up in the banking & financial services world, keep reading!Creative Thinkers: If your brain is always bubbling with out-of-the-box ideas and wild solutions, you’re our kind of person. We love disruptors who challenge the norm and bring fresh perspectives to the table.Customer Heroes: Our customers are our champions, and we need heroes who can understand their needs, deliver magical experiences, and go above and beyond to keep them happy.Team Players: We believe in the power of “we.” If you thrive in a collaborative environment, value different viewpoints, and enjoy being part of a spirited, supportive team, you’ll fit right in.How You'll Contribute:

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.

FinBox

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