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about.

I’m Mayank, Senior Consultant, Product at MiQ Digital in Bengaluru. I look for the person standing between a question and its answer, and build the thing that means they don’t have to stand there any more.

I did not start in product. I started as a business analyst in 2019, building an attribution model that measured whether people who saw a film’s digital ads actually turned up at the cinema. I spent two years being the person in the middle, the one everybody messaged when they needed a number. That is not a complaint. It is the single most useful thing that ever happened to my product instincts, because I know exactly what that work costs and exactly how invisible it is.

Everything since has been a version of removing it. An agent framework so analysts stop hunting across four systems for one answer. An AI development framework, so a product analyst can ship a UI change without waiting three weeks for an engineer. A healthcare AI stack, so a planner gets a compliant answer, with its reasoning, instead of a meeting.

None of it needed a frontier model. All of it needed knowing the domain well enough to tell which questions are worth automating and which ones are hard for a good reason.

work.

The things I have not built sit separately, under Ideas.

experience.

  1. Senior Consultant, Product (US Local Products)

    Apr 2026 – Present

    • Building a Healthcare AI stack (data, compliance, retrieval and agent surfaces) as the Healthcare product line shifts to AI-native features, so measurement and audience questions resolve without analyst intervention.
    • Shipped an AI development framework for webapp creation: upskilled product analysts on SDLC and CI/CD and built the guardrails (typed contracts, lint/test gates, shared design tokens) that let non-engineers deliver micro-frontend UI changes such as input forms end to end, cutting combined frontend and backend delivery time by 85%.

  2. Product Manager / Consultant (US Local Products)

    Jan 2024 – Mar 2026

    • Led 10+ member cross-functional teams building products that help US advertisers reach high-value Healthcare, Entertainment and DOOH audiences; delivered ~$90M in revenue including 2025 Healthcare releases (2 HCI updates, MiQ Health Segment v2) and an AI-powered Healthcare chatbot that cut analyst dependency for measurement queries.
    • Built an A2A agent framework to eliminate time analysts spent navigating fragmented data systems, enabling natural-language queries across compliance, wiki and measurement via Vertex AI; adopted Replit and Cursor to cut internal tool build time; founded MiQ’s AI Club to scale AI/ML literacy across teams.

  3. Associate Product Manager / Consultant (US Local Products)

    May 2022 – Dec 2023

    • Built the DOOH product suite to close advertiser gaps in out-of-home planning: aviation targeting, proximity, cross-channel, Search Sync and an automated RFP generator; grew DOOH from $2M to $5M (150% YoY, 2022–23) owning end-to-end PRD, sprint planning and stakeholder alignment.
    • Replaced manual pharma client reporting with an automated activation and measurement solution (~8 hrs/week saved per client, ~100 analyst hrs per run); built an Entertainment Planning Tool so planners could discover relevant content inventory in minutes, powered by a content and collaborative filtering recommendation engine.

  4. Senior Business Analyst

    Apr 2021 – May 2022

    • Replaced manual analyst workflows for $3–4M enterprise accounts with automated pipelines (PySpark, SQL) and self-serve dashboards (Google Data Studio, Apps Script), cutting recurring manual work 30–40% and freeing the team for higher-value analysis; onboarded and upskilled 5+ junior analysts.

  5. Business Analyst (incl. Internship)

    Jan 2019 – Mar 2021

    • Built a Movie Online-to-Offline attribution model proving digital ad ROI for film studios by measuring actual theatre footfall; gave a cybersecurity client real-time market impact visibility via a data breach dashboard ($500K account increment during COVID); built CRM segmentation models for personalised campaign targeting across auto and CPG brands.

earlier.

  1. IIT Kharagpur

    Jun 2018 – Jul 2018

    Research Intern, Recommendation Systems, ISE Department

    Researched graph kernel models to improve recommendation accuracy in sparse-data environments; benchmarked collaborative filtering approaches on RMSE, MAE, precision and recall. Those foundations directly shaped recommendation engine design in later roles at MiQ.

  2. IIM Lucknow

    Jun 2017 – Jul 2017

    Data Science & Analytics Intern

    Completed an intensive analytics programme covering R, statistics and econometrics; executed Harvard Business School case analyses and built 2 mini-projects plus a capstone on MBA salary trends, airline pricing dynamics and hotel industry performance.

  3. R.V. College of Engineering

    2015 – 2019

    B.E. Industrial Engineering & Management · 8.64/10 CGPA

    Relevant coursework: Product Management, Operations Management, Advanced Statistics, RDBMS, Data Analytics, Work Systems Design

tools.

AI & Product
Agent frameworks (A2A)RAG & retrieval designEvals & guardrailsAI enablementProduct strategyRoadmap & OKRsPRDsA/B testingGTM
Engineering & Data
PythonSQLPySparkRCI/CDMicro-frontendsBigQueryFirebase
Platforms
Vertex AIGCPCursorReplitDV360ADHTableauGoogle Data Studio
Ways of working
AgileScrumStakeholder managementCross-geo delivery (US/India)

Recognition

  • Finalist, Google Agentic AI Day Hackathon (2025)
  • Winner, Wequity सम AI Hackathon (2025)
  • MiQ Emerging Leaders Programme
  • NPTEL Gold Medalist (R Programming)

Away from the desk

  • Chess (Bengaluru Chess Club regular)
  • Running & trekking (3 Himalayan treks)
  • Speed cubing (Co-founder, RVCE Cube Society)

The cubing and the chess are probably not a coincidence. Both are pattern recognition under a clock.

elsewhere.

I like talking to people putting AI inside organisations that were not designed for it. mayanksagar26@gmail.com is the fastest way to reach me.