Senior Data Scientist
FinBox
- Gurgaon, Haryana
- Permanent
- Full-time
- 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.
- Data Analytics & Insights: Analyze large datasets to generate meaningful insights and measure business impact.
- Model Development & Experimentation: Design and deploy predictive models, leveraging statistical and machine learning techniques to drive business growth.
- Algorithm Development: Create and optimize algorithms to extract and process data, improving decision-making processes.
- Experimentation & A/B Testing: Conduct rigorous experimentation to refine products and optimize business strategies.
- Visualization & Reporting: Build dashboards and automated reports using visualization tools to communicate insights effectively.
- End-to-End Data Processing: Gather, clean, and pre-process data for insight generation and model building.
- Stakeholder Collaboration: Work closely with product, engineering, and business teams to translate informal requirements into problem statements and solutions.
- Model Deployment: Deploy ML models and ensure they are optimized for production and business applications.
- 8+ years of experience in data science, with a strong background in the finance or fintech sector.
- Expertise in Python/R, SQL, and Excel for data analysis, modeling, and automation.
- Proficiency in AWS & Git for cloud-based deployment and version control.
- Strong knowledge of statistical methods and machine learning techniques, including regression, clustering, decision trees, bootstrapping, and survival analysis.
- Hands-on experience with data visualization tools such as Tableau, Power BI, or open-source libraries.
- Strong problem-solving and communication skills to simplify complex models and insights for business stakeholders.
- Experience in deploying data science solutions at scale, with a focus on automation and real-time analytics.