Resume
Sameer Bhalerao
Senior analytics leader and AI systems builder with 11+ years turning complex data into strategic product decisions.
Summary
Senior analytics leader and AI systems builder with 11+ years turning complex data into strategic product decisions. 9-year track record at Amazon spanning marketplace growth, private brands, and payments — shipping analytics products used by hundreds of stakeholders across EU/NA/JP, authoring BRDs that shaped marketplace policy, and owning the full BI lifecycle from pipeline to C-suite QBR. Independently built and deployed four public AI-powered tools. Interested in roles at the intersection of data, AI, and product.
Experience
Sr. Business Intelligence Engineer — Selection Expansion (L6)
Jan 2024 – Apr 2026Amazon · Luxembourg
- Sole BIE owner for selection expansion analytics function across 17+ global Amazon stores; redesigned quarterly business reviews with new metric taxonomy (Platform GMS, offer breakdown, Contribution to 3P sales, selection quality) — drove 4 leadership cycles influencing broader product and business strategy.
- Rebuilt core selection identification logic fixing long-standing data inaccuracies across offers and funnel metrics, restoring trust in 20+ downstream reports used by Business Managers and engineering teams.
- Delivered entitlement calculations for a $2.5B Seller growth Big Bet project under strict timelines, forming the analytical foundation for 2026 annual operational planning discussions.
Sr. Business Intelligence Engineer — Amazon Private Brands (L5 → L6)
Jan 2021 – Dec 2023Amazon · Luxembourg
- First BIE hire for EU Private Brands; built and led the BI function (3 BIEs + interns) covering Product, Marketing, Supply Chain, and Finance across Europe, North America, and APAC.
- Delivered the APB-first Deals Performance Dashboard — defined product requirements and prioritised the build roadmap for four analytics tools used by 90+ users across 10 countries and 12 job families; global single source of truth for Private Brands deals analytics, saving 350+ hours/year.
- Built Catalog Defects and products-with-a-sale bridge uncovering ~€110M GMS opportunity, adopted by senior leadership for quarterly planning.
- Led Inventory Tracker Engine design and development in partnership with global supply chain teams, saving 1,000+ hours/year for EU Private Brands; extended to NA and APAC regions in V2.
- Promoted L5 → L6 in Q3 2022 (10 feedback providers: 4 × L7, 6 × L6); cited for SQL cube innovation reducing Private Brands weekly business review code from 20K to 1.3K lines, adopted org-wide across APB BI.
Lead Business Analyst — Amazon Pay / High-Frequency Commerce (L5)
Apr 2019 – Jan 2021Amazon · Bengaluru, India
- Led analytics for Amazon Pay and High-Frequency Commerce (Recharges & Bill Payments), supporting product, marketing, and operations teams across category launches, abuse prevention, and weblab decision-making.
- Designed and implemented the Downstream Impact calculation methodology for product launch decisions, enabling Go/No-Go decisions on 5 Pay experiments ($30M GMV stakes) — adopted by PMs as the standard framework for feature launches.
- Built a Python-based self-serve customer segmentation tool processing ~100 marketing campaigns/month; reduced campaign setup time by ~70%, saving ~3,000 hours/year for marketing and PM teams.
- Designed abuse-prevention rules for HFC Recharges combining multiple data sources to auto-cancel ~100K abusive orders/month (~2% of volume), significantly reducing incentive fraud while minimising false positives.
Business Analyst — Amazon Pay / High-Frequency Commerce (L4)
Jan 2017 – Apr 2019Amazon · Bengaluru, India
- Built end-to-end data pipelines, 5 dashboards with 15+ views and a 25+ query self-serve library to support the launch of eight HFC categories (Prepaid Recharge, Bill Payments, Flight Bookings etc.) — became the foundational analytics suite driving 50+ launch campaigns and incremental product development for this $2B business.
- Delivered weblab analysis for 3 CX improvements leading to high-confidence product decisions; identified $5M in accounting corrections through deep dives involving Accounting, Business, and Nodal teams.
Decision Scientist (Analyst → Senior Analyst)
2014 – 2016Mu Sigma Business Solutions · Bengaluru, India
- Led analytics for two Fortune 500 retail and airline clients; built segmentation, demand forecasting, and marketing mix models influencing multi-million-dollar spend decisions.
Education
B.E. — Electrical and Electronics
Birla Institute of Technology, Mesra
Ranchi, India · 2010 – 2014
First Class with Distinction
Skills
AI Products & Applied AI
Multi-Agent ArchitectureLLM SystemsOllamaPrompt EngineeringLangChainLangGraphRAG Patterns
Data Products & Strategy
Data Products OwnershipMetrics Design & GovernanceBI SystemsETL PipelinesDashboard ArchitectureSelf-Serve Analytics
Analytics & Engineering
SQLPythonData ModelingAmazon RedshiftQuickSightA/B TestingPandasPlotly
Tools & Technologies
StreamlitDuckDBSQLiteGoogle Sheets APINext.jsTypeScriptGitAWSdbt
Leadership & Communication
Stakeholder LeadershipC-suite QBRCross-functional LeadershipTeam BuildingBRD AuthoringGo/No-Go Frameworks
Certifications
- dbt Analytics Engineering
- Ollama — Local LLM Inference & Prompt Engineering
- AWS BI Technology Specialist
- LangGraph and LangChain Design and Implementation
- AI For Everyone — DeepLearning.AI
- Agentic Coding Expertise — Claude Code, Codex and Copilot
Selected Achievements
- ~€110M GMS opportunity uncovered via catalog defect analytics — adopted by senior leadership
- $2.5B Seller growth Big Bet — delivered entitlement calculations forming annual planning foundation
- 1,000+ hours/year saved via Inventory Tracker Engine, extended to NA and APAC
- 350+ hours/year saved via Deals Performance Dashboard serving 90+ users across 10 countries
- ~3,000 hours/year saved via Python self-serve segmentation tool for marketing teams
- ~100K abusive orders/month auto-cancelled via abuse-prevention rules for HFC Recharges
- Promoted L5 → L6 at Amazon with 10 feedback providers (4 × L7, 6 × L6)
- 4 independent AI products independently built, deployed, and publicly live