Staff Data Scientist, AI-Driven Legal Platform

Crosby; New York (NY); On-site; USD 200,000 - 300,000; Full time

Job summary

Crosby is seeking a Data Scientist to advance our AI-first legal platform. You will design, train, and evaluate models that power our systems, working across data definition, labeling, and production deployment.

You will collaborate with engineers, product teams, and legal experts to translate complex workflows into robust machine learning solutions, ensuring accuracy and continuous improvement in real-world use.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Python

Machine Learning

NLP

Data Analysis

Communication

Tools

LLMs

Data Pipelines

Job description

Crosby is seeking a Data Scientist to advance our AI-first legal platform. You will design, train, and evaluate models that power our systems, working across data definition, labeling, and production deployment.

You will collaborate with engineers, product teams, and legal experts to translate complex workflows into robust machine learning solutions, ensuring accuracy and continuous improvement in real-world use.