Data Scientist

Objective

We are seeking a highly driven data science and analytics professional with 6-9 years of experience in leading AI/ML, credit strategy, product automation, and analytics delivery across financial services. Demonstrated expertise in building end-to-end customer-level scoring frameworks, driving business transformation through data, onboarding alternative data providers and delivering high-visibility projects

Roles & Responsibilities:

• Develop machine learning and rule-based credit scorecards for secured and unsecured loans.
• Strong command over PySpark, Python, and SQL for large-scale data processing, data engineering and analytics. Built segmentation, eligibility models, and monitoring dashboards.
• Possess deep expertise in bureau data interpretation. Applied bureau insights across credit policy design, risk assessment, cross-sell targeting, underwriting strategies and others
• Lead data-driven campaign analytics across products by integrating bureau, app journey, and other data sources. Develop cross-sell and upsell strategies through precise segmentation and automation. Build lead scoring and prioritization logic to improve targeting and conversion.
• Built automated collections dashboards by integrating LMS and collections systems to track key KPIs.
• Partner with the data engineering team to streamline access to high-volume datasets from Big Data. Drive scalable solutions using PySpark, pandas, and cloud tools for data wrangling and ML training
• Built scalable data pipelines to aggregate internal and external data sources. Design automated daily MIS reporting pipelines across various product journeys.
• Collaborate with product, risk, and tech teams to launch AI-driven initiatives
  

Knowledge & Skills:

• Experience: 3-5 years in lending, credit analytics, and financial data science.
• Languages & Tools: Python, PySpark, SQL, Looker Studio, Power BI.
• Data Expertise: Deep understanding of credit bureau data, banking data, customer segmentation, and data platform architecture.
• Process Knowledge: Familiarity with credit policy design, loan lifecycle MIS, and external vendor integrations.
• Innovation: Exposure to GenAI tools and use cases in financial services is a plus.
• Communication: Strong skills in storytelling, requirement gathering, and documentation.
• Dashboarding: Experience with dashboard creation in Power BI / Looker Studio (basic to intermediate proficiency).

  Role & responsibilities