Raoul Maldonado

Summary

Senior data scientist with 9+ years shipping machine learning models to production and owning experimentation strategy for consumer-facing products. Partners closely with engineering and product leadership to translate ambiguous problems into measurable, deployed solutions, and has mentored a growing bench of junior data scientists. Comfortable owning a system end-to-end, from research to production monitoring.

Skills

• Languages & Tools: Python (pandas, scikit-learn, PyTorch), SQL, Docker, Airflow, MLflow
• ML & Experimentation: production model deployment, A/B testing platform design, causal inference, deep learning for ranking/recommendations
• Leadership: cross-functional partnership with engineering and product, mentoring, technical roadmap ownership

Experience

Staff Data Scientist — Junction Analytics (Apr 2023 – Present)

• Own the company’s experimentation platform, supporting 200+ A/B tests per year across product and marketing teams
• Architected and shipped a recommendation model to production that lifted click-through rate by 14% for 2M+ monthly active users
• Lead a working group of 5 data scientists defining modeling standards, code review practices, and a shared feature store
• Partner directly with the VP of Product to prioritize the ML roadmap, translating business goals into a quarterly experimentation plan
• Mentor 4 mid-level data scientists, two of whom were promoted to senior within 18 months

Senior Data Scientist — Solstice Travel (Feb 2019 – Mar 2023)

• Built and deployed a dynamic pricing model that increased booking margin by 7% ($3.4M annualized), owning it from prototype through production monitoring
• Designed the team’s first standardized A/B testing framework, reducing time-to-launch for new experiments from 3 weeks to 4 days
• Partnered with engineering to migrate batch scoring jobs to a real-time inference service, cutting model latency from minutes to under 200ms
• Mentored 2 junior data scientists and led the team’s internal ML lunch-and-learn series

Data Scientist — Rivergate Media (Jul 2016 – Jan 2019)

• Built a content recommendation model that increased average session length by 11% across the media platform
• Ran and analyzed 40+ A/B tests on content ranking and UI changes, establishing the team’s first experimentation guidelines
• Developed churn and lifetime value models used by the marketing team to prioritize retention campaigns

Education

• M.S. in Data Science, Brookline University, 2016
• B.S. in Applied Mathematics, Northgate University, 2014

Certifications / Projects

• Built and open-sourced an internal experimentation library for sequential A/B testing, adopted by 3 teams at Junction Analytics
• Regular mentor and interviewer for Junction Analytics’ university data science recruiting program