Data Scientist

Job Summary:
We are seeking a Senior Data Scientist to lead the design and validation of AI-driven product capabilities within the legal domain. This role focuses on defining what to build and why, leveraging machine learning, NLP, and large language models (LLMs) to solve complex legal workflows. You will drive experimentation, modeling, and evaluation, partnering closely with engineers to translate validated approaches into scalable, customer-facing solutions.


Key Responsibilities:
• Lead experimentation and model development for AI/ML solutions in legal products.
• Design and evaluate NLP, LLM, and generative AI approaches, including RAG and prompt strategies.
• Define agentic workflows and reasoning strategies for multi-step legal tasks.
• Define retrieval strategies, including hybrid search combining semantic and lexical approaches, and evaluation metrics such as relevance and ranking quality.
• Analyze large-scale legal datasets to extract insights and improve model performance.
• Establish best practices for model evaluation, validation, and benchmarking.
• Translate experimental results into clear product recommendations and business impact.
• Collaborate with product, legal experts, and engineers to align solutions with user needs.
• Mentor team members and provide technical leadership in data science and AI.


Required Qualifications:
• 7-10+ years of data science experience, with a career foundation in NLP and the past 4-5 years focused strongly on Generative AI data science.
• Experience designing agentic workflows and applying generative AI techniques, including prompt engineering and end-to-end RAG system development.
• Strong experience working with unstructured data, including text and documents, document processing, NLP, embeddings, retrieval, and agentic systems.
• Strong experience creating production-grade ML systems at scale.
• Strong LLM, Generative AI, and RAG deployment experience, including implementation and end-to-end evaluation.
• Experience with the complete deployment lifecycle, including product development, production maintenance, and new feature development.
• Experience working alongside ML engineers throughout the production deployment and lifecycle.
• Strong Python programming skills.