Experience

A progressive path

From analytics and product ops to venture investing. Start at Apple, then drag or scroll right through the arc.

jasonr34@mit.edu LinkedIn GitHub

2017 – 2018 · New York, NY

Apple

Data Scientist

  • Designed and programmed global transit ETLs and machine learning integration to increase data feed throughput 75% YoY.
  • Partnered with ops to launch new markets, visualizing performance and adoption metrics via Tableau.

2018 – 2020 · New York, NY

Lunatix

Manager, Analytics

Acquired by Sports Illustrated

  • Drove 22% YoY reduction in customer acquisition cost through marketing analytics informing channel optimization.
  • Supported CEO and board on growth strategy, driving 6x revenue growth from $500k to $3M ARR through user acquisition optimization and A/B testing.

2020 – 2022 · New York, NY

HearMeCheer

Co-Founder, Chief Operating Officer

  • Raised $400k seed funding at $8M valuation and co-authored a patent on audio data aggregation technology.
  • Generated $500k revenue from ESPN, NY Red Bulls, LAFC, and DNC through strategic sales and product prioritization.
  • Led a 4-person technical team and managed client relationships, delivering product enhancements on compressed timelines.

2021 – 2022 · New York, NY

Compass Real Estate

Business Intelligence Engineer · FP&A, Product

  • Delivered executive KPIs and budget forecasts with 150 bps accuracy, supporting the CFO's quarterly planning and resource allocation.
  • Reduced gross margin model run-time 95% (5 hours to 15 minutes), enabling real-time profitability analysis.
  • Partnered with the CFO's office to prepare research ahead of quarterly earnings calls, anticipating analyst questions.

2022 – 2025 · New York, NY

Amazon

Business Intelligence Engineer · Ads Forecasting Economics & Science, Pubtech

  • Forecasted $10B+ DSP revenue with under 5% MAPE using hierarchical time-series models, directly informing annual planning.
  • Delivered quarterly forecast outputs to VP-level stakeholders and partnered with economists on deep-dives informing 9-figure investment decisions.
  • Fine-tuned an AI model on company financial data with a Slack interface for self-service questions, reaching 500+ queries per week across 50+ finance partners.
  • Developed a classification model improving ad delivery by 450 bps and reducing under-delivery costs by $1.7M monthly.

2025 – Present · Cambridge, MA

MIT Sloan

MBA Candidate · Class of 2027

  • Fintech Club, VC & PE Club, AI & ML Club, Technology Club, Blockchain Club, Ski Club.
  • Teaching Assistant for 15.714 (Executive MBA Competitive Strategy), Spring 2026.
  • Cross-registered into Course 22 for Intro to Sustainable Energy and Applied Nuclear Physics.
  • Partner at TNT (tnt.so), focused on Harvard and MIT student founders.

Earlier: B.S. Sport Management, Minor in Economics · UMass Amherst · 2013 – 2017

2026 · New York, NY

Flybridge

Venture Capital Investor · Intern

  • Authored theses on edge AI infrastructure, continual learning, and agentic file systems and presented to the investment team.
  • Evaluate direct (seed, series A–C) investments across AI infrastructure, vertical AI, and embodied AI system spaces. Prepare market maps, investment memorandums, and present findings to IC.
  • Led diligence on early-stage robotics and infrastructure startups, producing investment memos with competitive analysis and recommendations.
  • Sourced and conducted expert conversations with AI researchers and operators for diligence and thesis feedback.
  • Built a Slack bot that lets the team interact with each other's Granola notes, accelerating diligence and IC reviews.