Rahul Agarwal

About Rahul Agarwal

I work at the intersection of data science, product, and growth, building behavior-driven decision systems that improve relevance, activation, and retention at scale.At Meesho, I’ve led analytical system design across real-time personalization, ranking relevance, dynamic discounting, and experimentation, translating complex behavioral signals into scalable, autonomous solutions. My work has driven measurable uplifts in 1ODNR, habit formation, engagement, and feed reliability, while reducing manual operations and DS dependency.I specialize in:• Applied data science for relevance & ranking• Cohort modeling & behavioral segmentation• Experiment design, guardrails & metric deep-dives• SQL-heavy data modeling and analytical pipelines• Cross-functional execution with DS, Product & EngineeringFocused on Applied / Product Data Scientist roles solving personalization, ranking, and growth problems in high-scale consumer products.

Experience

1. Senior Business Analyst

   Meesho

   Jan 2026 — Present · Bengaluru, IN

   Previously Business Analyst II and Business Analyst I; scope expanded with promotions across the same problem space.* Own applied data science initiatives across large-scale discovery surfaces impacting millions of users daily.* Build production-grade, behavior-driven decision systems for personalization, ranking, and lifecycle optimization at scale, working closely with Data Science, Product, and Engineering.* Designed and launched an autonomous dynamic incentive engine using behavioral signals (session depth, inactivity, WL/ATC), driving +3pp uplift in habit formation (4OD/1OD) while reducing discount burn.* Developed a propensity-based modeling framework (logistic regression / tree-based) to predict conversion likelihood and enable differential, need-based incentive allocation.* Engineered a self-regulating 15-day eligibility and decay mechanism to manage offer persistence, prevent misuse, and support clean experimentation without manual intervention.* Led real-time relevance improvements for 0–1 order users by enabling in-session cohort updates and ranking refreshes, reducing early-session drop-offs.* Contributed to feed and search ranking systems by validating high-signal behavioral features and supporting feature onboarding and experiment design.* Designed and analyzed A/B experiments across intent feed and ranking refresh strategies, driving measurable uplifts in 1ODNR, activation, engagement, and bounce rate.* Diagnosed and resolved Meta remarketing feed reliability issues, improving catalog match rate from 50% → 97% and unlocking higher CTR and incremental DAU.* Built SQL-heavy analytical pipelines and automated reporting to improve data reliability and reduce ad-hoc analysis.

Education

• Subodh Public School

  X, General

  2018

• Subodh Public School

  XII, Commerce

  2020

• Scaler

  Data Science and Machine Learning

• Commerce College Jaipur

  Bachelor's degree, Computer Programming/Programmer, General

  2020 — 2023