Senior Data Scientist — Bayesian Modeling | Leading Global Trading Firm (NYC)

Stabile Search•New York, NY

10d•Onsite

About The Position

My top-tier client is growing their new data science team and they are looking for a Senior Data Scientist. If you are excited about a role at a top quantitative trading firm where you will have ownership over new data science projects in a supportive environment, then this is the opportunity for you. My client is hiring a Data Scientist to join a small, high-impact client-facing data science team in New York. The firm has world-class capabilities in large-scale, frequentist statistical modeling. What's missing is the Bayesian side: extracting nuanced insights from smaller, looser, messier datasets that traditional big-data approaches leave untouched. That's where you come in. You'll build models and tools that turn these underutilized data sources into differentiated views for the firm's clients, particularly discretionary investors who need more than what large-dataset analytics can offer. Think marrying two small, overlapping datasets to uncover signals no one else has found. You'll report directly to the team lead, work alongside the firm's senior market strategists, and engage with clients, a rare seat that combines deep technical work with real visibility. This is not a quant research or alpha-generation role; it's a highly technical, client-oriented position using market and alternative data to drive the firm's client offering.

Requirements

3–7 years of professional experience as a data scientist or in a similar quantitative modeling role.
Hands-on experience with Bayesian statistics and modeling in a professional setting.
Strong programming skills in Python or R.
Grit, intellectual curiosity, and comfort building from scratch on a small team.

Nice To Haves

Advanced degree strongly preferred — ideally a PhD in Statistics, Computer Science, Math, Operations Research, Computational Social Science, or a related field.
Experience working with consumer, marketing, or otherwise messy real-world data is a plus.
Backgrounds in tech are especially welcome.
No finance experience required.

Responsibilities

Build models and tools that turn underutilized data sources into differentiated views for the firm's clients.
Extract nuanced insights from smaller, looser, messier datasets.
Marry two small, overlapping datasets to uncover signals.
Engage with clients.
Use market and alternative data to drive the firm's client offering.