Member of Technical Staff, Data Science

About Crosby Crosby is built on a simple conviction: a great legal system is the watermark of a great society — and the best legal work comes from combining human expertise with the right technology, not replacing one with the other. Crosby is the first AI-native law firm, helping ambitious companies like Cursor, Ramp, and Cognition sign commercial contracts faster. Legal work is both art and science, and we're mapping the frontier between the two — codifying what can be systematized, amplifying human judgment where it matters most. That's why the right way to bring AI into law isn't to sell software and walk away. It's to own the outcome together: higher-quality work, delivered faster. We build proprietary tools and human-in-the-loop workflows that change what's possible for corporate legal teams. Crosby was founded by Ryan (Stanford Law, Cooley, startup GC) and John (Penn, first 15 engineers at Ramp). Help us transform one of society's most important industries. About the role As a Data Scientist at Crosby, you'll play a critical role in developing the models and data systems that power our AI-driven legal platform. You’ll work across the full lifecycle — from data definition and labeling strategy to model development, evaluation, and iteration in production. You’ll partner closely with engineers, product teams, and legal experts to translate complex legal workflows into structured machine learning systems. Beyond modeling, you’ll help ensure our systems are accurate, reliable, and continuously improving in real-world use. What you'll do Develop evaluation systems: Build metrics, benchmarks, and experimentation frameworks to measure and improve model performance. Drive data strategy: Partner with legal and product teams to define labeling schemas, curate high-quality datasets, and improve data pipelines. Support production systems: Work closely with engineering to deploy models, monitor performance, and iterate based on real-world usage. Apply AI pragmatically: Leverage LLMs and other modern techniques to solve product problems, balancing sophistication with reliability and speed. Collaborate cross-functionally: Partner with engineering, product, and legal teams to deliver end-to-end systems that improve customer outcomes. Who you are 1–5 years of experience in data science, machine learning, or applied NLP, ideally in a fast-paced startup environment Strong foundation in machine learning, statistics, and data analysis, with proficiency in Python Hands-on experience working with LLMs, NLP systems, or unstructured text data Experience working across the full ML lifecycle — from data curation and experimentation to deployment and monitoring Highly analytical with strong problem-solving skills and the ability to translate ambiguous problems into structured solutions Strong communicator who can collaborate effectively with both technical and non-technical stakeholders Benefits & Perks Unlimited PTO Lunch & dinner in the office every day Medical insurance (multiple plan options through Anthem & Cigna) HSA or FSA, depending on your plan choice Dental insurance Vision insurance One Medical membership 401(k) match In-office desk setup stipend Equal Opportunity Crosby is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the New York City Fair Chance Act. Pursuant to New York Labor Law Section 194-b, the US Pay Range for this position is listed in the job post. Final compensation will be determined based on skills, experience, and qualifications.