Headline

Financial Data Scientist | Credit Portfolio Analytics · P&L · ADB · CECL | Databricks · PySpark · SQL | BITS Pilani

About

I build financial data infrastructure that drives portfolio decisions at scale. As a Data Scientist 2 at Bread Financial, I work across a $17B consumer credit portfolio — designing the data products that finance leadership uses to manage P&L, credit loss provisioning, capital allocation, and portfolio performance. In 24 months I was promoted twice — from intern to Data Scientist 2 — owning the development of: → Account-level P&L reporting layer used by the CFO and finance leadership in monthly portfolio reviews → Average Daily Balance (ADB) framework reconciled to Fiserv, feeding P&L, credit loss, and capital allocation analytics → Life-of-loan data pipeline providing CECL credit loss forecasting inputs to the modeling team → Capital allocation analytics identifying loss-concentrated segments, enabling finance leadership to reallocate promotional spend toward higher risk-adjusted-return books → 400+ variable financial Datamart cutting manual data preparation time by 50% → Automated reporting pipelines compressing monthly financial close from 2 days to a few hours My background sits at the intersection of financial analytics and data engineering — I translate complex credit portfolio economics into governed, scalable data products that non-technical finance stakeholders can act on directly. Education: M.Sc. Economics & Finance + B.E. Electronics & Communication Engineering, BITS Pilani (2024) Open to roles in PE Portfolio Operations, credit analytics, and financial data architecture.

Location

Bengaluru

AI stack

anthropic apis

claude code

github copilot

hugging face

Work experience

Data Scientist 2 at Bread Financial, Nov 2025 - Present · 10 mos, Bengaluru, Karnataka, India · Hybrid, Building and governing financial data products across a $17B consumer credit portfolio used by finance leadership for monthly portfolio decisioning. Key contributions: → Built account-level P&L reporting layer used by finance leadership in monthly portfolio reviews — enabling the team to interrogate performance at client, product, and account level → Built capital allocation analytics identifying loss-concentrated client, product, and account segments — enabling finance leadership to reallocate promotional spend toward higher risk-adjusted-return books and reduce exposure to persistently loss-concentrated cohorts → Compressed monthly financial reporting cycles from 2 days to a few hours by automating P&L and credit loss data pipelines → Reduced manual reporting refresh dependency by 90% through automated and scheduled data pipelines with embedded loss estimation rules and governance checks → Led migration of legacy Power BI and Alteryx workflows to Databricks Dashboards and Lakehouse Apps, reducing dashboard latency by 80%

Data Scientist 1 at Bread Financial, Jun 2024 - Nov 2025 · 1 yr 6 mos, Bengaluru, Karnataka, India · Hybrid, Built the core financial data foundation for a $17B consumer credit portfolio — designing the governed data infrastructure that enabled P&L, credit loss, and capital allocation analytics at scale. Key contributions: → Co-developed the Average Daily Balance (ADB) framework from daily transaction logs in collaboration with finance and data engineering teams, reconciling outputs to Fiserv daily balance numbers — feeding P&L, credit loss, and capital allocation analytics across the portfolio → Built the life-of-loan data pipeline providing CECL credit loss forecasting inputs to the modeling team — enabling accurate long-term loss estimation across the portfolio → Engineered a 400+ variable financial Datamart cutting manual data preparation time by 50% and accelerating credit risk analytics delivery → Built time-series models for reward point breakage improving financial planning inputs for 10+ key clients and strengthening forecast traceability for finance stakeholders

Data Science Intern at Bread Financial, Jan 2024 - Jun 2024 · 6 mos, Bengaluru, Karnataka, India · Hybrid, Built foundational finance data pipelines during a 6-month internship that led to a full-time offer and a subsequent promotions. Key contributions: → Built loan lifecycle tracking pipeline feeding the modeling team's CECL credit loss analysis → Standardized reusable SQL transformation logic for monthly P&L packs, cutting duplicate calculation effort by 40% and improving consistency across finance reporting → Redesigned PySpark ETL pipelines reducing data delivery latency by 98% (8.5 hrs → 30 min), ensuring timely financial dashboard refreshes

Education

Bachelor of Engineering - BE, Electrical, Electronic and Communications Engineering Technology/Technician, Birla Institute of Technology and Science, Pilani - Goa Campus

Master of Science - MS, Economics, Birla Institute of Technology and Science, Pilani - Goa Campus