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Salary: USD 200,000 - 250,000 / annual
Crosby is an AI-native law firm transforming corporate legal services by combining human expertise with proprietary technology. The company helps ambitious companies like Cursor, Ramp, and Cognition sign commercial contracts faster through AI-powered workflows and tools.
As a Data Scientist at Crosby, you will play a critical role in developing the models and data systems that power the AI-driven legal platform. You'll work across the full machine learning lifecycle—from data definition and labeling strategy to model development, evaluation, and iteration in production.
Key responsibilities include:
- 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.
You'll work at the intersection of machine learning, product, and legal expertise, translating complex legal workflows into structured machine learning systems. The team prioritizes speed, ownership, and high standards—shipping quickly while maintaining rigor.
Crosby is backed by Sequoia, Index Ventures, and Bain Capital Ventures.
REQUIREMENTS:
- 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
