Hi, I’m Rina Lukina. I graduated from the University of Southern California, then dove straight into the world of quantitative data analysis. Over the past several years I’ve been building statistical models, running backtests, designing risk frameworks, and shipping production-ready code that turns noisy data into actionable signals. I’m fluent in Python, SQL, R, and common ML toolkits. My day-to-day looks like: cleaning messy feeds, engineering features, testing hypotheses, tuning models, explaining results to non-technical teams, and keeping systems humming in production. I’m the kind of operator who gets into the weeds when needed, then zooms out to connect work to business outcomes.

I also earned a Master’s in Finance, which gave me a tight handle on valuation methods, portfolio construction, derivatives, and capital markets mechanics. That training helps me translate model outputs into funding decisions and risk limits that make sense on a P&L.

Recently I added a new lane: I’m a co-investor in a boutique beauty studio. What started as a side hustle turned into a legit venture where I’m helping with strategy, ops, metrics, and growth plans. I’m hands-on with unit economics, pricing, staffing strategy, appointment flow, marketing experiments, and basic bookkeeping. My role blends pragmatic business sense with data-driven testing — think A/B tests for promotions, dashboarding for daily bookings, and tight tracking of customer lifetime value. It’s a fresh, fun contrast to the high-frequency world, yet the core skill is the same: measure what matters, iterate fast, keep it simple.

I bring a no-nonsense, results-first mindset. I like clean models, clean processes, and projects that actually move the needle. I’m also down-to-earth and enjoy trading a bit of industry jargon for plain talk when that helps get things done. If you want specifics about my quant work, the finance background, the studio, or next steps, tell me which piece to dig into and I’ll lay it out.