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Siddharth Mohan

@siddharthmohan

I spend my days convincing data to tell the truth. I build experimentation and analytics systems for Product and GTM functions. I like building.

India

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At Cockroach Labs, I built an ICP propensity model that lifted MQL-to-Opportunity conversion by 9–12% and a Snowflake MCP server that reduced ad hoc analytics requests by 37%. I also designed AI-powered campaign experiments that increased sequence step 2-to-step 3 conversions by 15%.

Across Media.Net, Ugam, and Mu Sigma, I've led global analytics teams, built experimentation and machine learning frameworks, and turned product, marketing, and operational data into measurable revenue and profitability gains.

Experience

Work history, roles, and key accomplishments

Senior Data Scientist, Product and GTM Analytics

Cockroach Labs

Nov 2023 - Apr 2026 (2 years 5 months)

Built an ICP propensity model for account targeting, driving a 9-12% lift in MQL-to-Opportunity conversion. Designed A/B tests for AI-powered sequencing campaigns, increasing sequence step 2 to step 3 conversions by 15%.

Python SQL Snowflake A B Testing Machine Learning Predictive Analytics Funnel Analysis MCP Servers

Associate Manager, Product Analytics

Media.Net LLC

Dec 2021 - Sep 2023 (1 year 9 months)

Led a hybrid team of Product Analysts and Ad Operations specialists, establishing experimentation frameworks. Designed A/B tests for ad fallback strategies, reducing campaign failure rate from 85%+ to ~64% and increasing ARPU from $0.29 to $0.44.

A B Testing Looker Product Analytics Ad Operations Experimentation Frameworks Executive Dashboards

Lead Data Analyst

Ugam (a Merkle Company)

Aug 2019 - Nov 2021 (2 years 3 months)

Led a global team of Data Scientists to optimize email campaign performance through engagement propensity modeling and A/B testing. Built an industry-agnostic machine learning automation framework within R Server, standardizing model development workflows for 1000+ analysts.

R Logistic Regression A B Testing Machine Learning Multi Touch Attribution Campaign Analytics

Decision Scientist

Mu Sigma

Jul 2016 - Aug 2019 (3 years 1 month)

Led an analytics team to develop an enterprise Cost-to-Serve model using activity-based costing, improving Grocery department profitability by 3.7 percentage points. Built a hierarchical NLP classification pipeline for real-time store incident monitoring, achieving an F1-score of 0.88.

NLP Machine Learning Ensemble Models R Shiny Cost to Serve Modeling Activity Based Costing