Jan 2024 – Sep 2025 · 1 yr 8 mos · San Francisco Bay Area

• Promoted to lead the subscription business.
• Own full P&L, operations, and product strategy (multi million subscribers, multi billion GMV).
• Achieved profitability and accelerated QoQ growth by double digits within six months of starting.
• Led Rappi’s largest commercial partnerships, hitting 100% of our 18-month growth targets in under 12 months.
• Scaled a high-performing, fast-paced, cross-functional team across Data Science, Operations, and Product.
• Regularly brief C-suite on growth, pricing, and retention - translating insights into clear operating plans and strategy.
• Rappi is a leading consumer tech delivery company, most recently valued at $5.2B with backers including YCombinator, Softbank, Andreessen Horowitz, and Sequoia Capital.

Jan 2023 – Jan 2024 · 1 yr · San Francisco Bay Area

• Designed and scaled an experimentation program to A/B test subscription pricing, onboarding, and incentives
• Built forecasting models for subscriber acquisition, churn, and revenue; used regularly for growth management and financial planning.
• Defined and operationalized KPI's that became core operating metrics, aligning product, finance, and ops teams through shared measurement.
• Built core analytics infrastructure powering all subscriber dashboards and reporting; reduced time to insight by 80%.

Jan 2022 – Jan 2023 · 1 yr · New York City Metropolitan Area

• Led data science strategy across portfolio companies; mentored junior team members and set technical direction.
• Created NLP models from review data to predict churn and upsell opportunities.
• Increased qualified sales pipeline by 18% through predictive scoring and better lead targeting..
• Conducted investment diligence by modeling LTV, NRR, and sales growth using alternative data sources
• Built scalable scraping pipelines to expand lead lists and improve conversion rates.

Jan 2018 – Jan 2022 · 4 yrs · San Francisco Bay Area

• Built systematic equity models using quality and valuation frameworks to identify undervalued companies.
• Led mid-frequency index arbitrage research and execution; achieved 90%+ prediction accuracy on index rebalances.
• Synthesized insights for portfolio managers and investment committee to guide allocation decisions.
• Owned full research pipeline: data sourcing, feature engineering, backtesting, and signal deployment.

Jan 2017 – Jan 2018 · 1 yr · San Francisco Bay Area

• Created ML models to predict churn with >80% accuracy.
• Developed GitHub’s first unified revenue database across self-serve and enterprise channels.
• Led analytics for product strategy; launched the first free-tier plan.

Jan 2015 – Jan 2017 · 2 yrs · Greater New York City Area

• Built regression models to identify mispriced assets and support pricing decisions across trading desks.
• Researched macroeconomic trends and market events to forecast asset price movements and volatility.
• Synthesized quantitative insights for traders and risk managers to inform trade execution and hedging strategy.
• Gained early exposure to high-pressure decision-making and fast-paced financial operations.