Hi, I'm Tanmay Bharadwaj, a Product & Systems Analyst focused on decision-heavy product workflows and architecture. I enjoy diagnosing structural issues in complex systems, decomposing problems into layered decision layers, and balancing automation with human judgment to deliver scalable, trusted outcomes in delivery platforms. I thrive in spaces where clarity of decision making is critical, and I aim to fix architectural and system-level bugs by rethinking decision flows, documenting the rationale, and embedding human-in-the-loop safeguards.

Tanmay Bharadwaj

Hi, I'm Tanmay Bharadwaj, a Product & Systems Analyst focused on decision-heavy product workflows and architecture. I enjoy diagnosing structural issues in complex systems, decomposing problems into layered decision layers, and balancing automation with human judgment to deliver scalable, trusted outcomes in delivery platforms. I thrive in spaces where clarity of decision making is critical, and I aim to fix architectural and system-level bugs by rethinking decision flows, documenting the rationale, and embedding human-in-the-loop safeguards.

Available to hire

Hi, I’m Tanmay Bharadwaj, a Product & Systems Analyst focused on decision-heavy product workflows and architecture. I enjoy diagnosing structural issues in complex systems, decomposing problems into layered decision layers, and balancing automation with human judgment to deliver scalable, trusted outcomes in delivery platforms.

I thrive in spaces where clarity of decision making is critical, and I aim to fix architectural and system-level bugs by rethinking decision flows, documenting the rationale, and embedding human-in-the-loop safeguards.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
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Work Experience

Decision Reliability Design – Offline Resilient AI Systems at Independent Project
January 1, 2025 - Present
Identified a systemic failure in AI products where connectivity loss causes abrupt breakdowns or unsafe overconfidence, leading to broken trust and unreliable decision-making. Developed a connectivity-aware, layered decision architecture that governs AI behaviour based on capability boundaries, risk level, and uncertainty instead of assuming constant cloud access. Built a system that degrades gracefully offline, preserving user intent, calibrating confidence, and safely deferring high-risk actions while continuing low-risk analysis locally. Prototyped end-to-end continuity and recovery flows that reconcile offline assumptions and restore full capability once connectivity is re-established.
Post Rejection Learning System Design – Hiring Platforms at Independent Project
January 1, 2025 - Present
Identified a systemic gap in hiring platforms where candidate rejection is treated as a terminal state, leading to repeated low-quality applications, recruiter overload, and declining decision quality at scale. Implemented a layered post-rejection decision architecture that infers safe rejection categories, counterfactual guidance, resume signal weaknesses, and interview-stage gaps without exposing recruiter intent. Built a candidate learning memory system to track historical rejection patterns and signal gaps over time, enabling learning to compound instead of resetting with each application. Prototyped an end-to-end flow that synthesizes structured signals into a post-rejection learning report, balancing candidate guidance, legal safety, operational scalability, and human-in-the-loop controls.
End to End Decision System Design – Consumer Delivery Platforms at Independent Project
January 1, 2025 - Present
Diagnosed structural decision bottlenecks in post-order product workflows where ambiguity, delayed verification, and manual review created high operational cost and customer friction. Designed a layered decision architecture that separates independent signals (input integrity, context, behavior) and avoids brittle, single-signal decisioning. Built a fusion-based decision flow with human-in-the-loop controls, decoupling immediate customer resolution from deferred verification to protect both CX and system integrity. Prototyped the end-to-end system to stress-test failure modes, ownership boundaries, and scalability before any production assumptions.

Education

BBA – Analytics and Big Data at UPES (University of Petroleum and Energy Studies), School of Business, Dehradun
January 1, 2022 - January 1, 2025

Qualifications

McKinsey Career Forward Program
January 1, 2025 - January 30, 2026
AI Mastermind Workshop
January 1, 2025 - January 30, 2026
End to End Data Analytics Course
January 1, 2026 - January 30, 2026

Industry Experience

Software & Internet, Professional Services, Education

Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
See more