Data Scientist

We are seeking a Senior Data Scientist to lead the vision, strategy, and execution of advanced AI and machine learning initiatives that power next-generation legal technology solutions. This highly influential role operates at the intersection of research, product strategy, and engineering, driving innovations in large language models (LLMs), retrieval-augmented generation (RAG), information extraction, document understanding, and agentic AI systems.

As a senior technical leader, you will define and evaluate AI approaches that transform complex legal and regulatory content into actionable intelligence. You will guide strategic decision-making, champion experimentation, establish best practices for AI quality and governance, and mentor other data scientists while partnering closely with product, engineering, legal experts, and executive leadership.

The ideal candidate combines deep expertise in machine learning, natural language processing, and generative AI with the ability to translate cutting-edge research into scalable products that deliver measurable business value.

Key Responsibilities

• Lead the strategic direction and technical roadmap for AI, machine learning, and generative AI initiatives across legal and regulatory product offerings.
• Design, develop, and evaluate advanced ML, NLP, and LLM-based solutions for legal reasoning, document analysis, classification, extraction, summarization, and workflow automation.
• Drive experimentation and innovation involving RAG architectures, prompt engineering, agentic systems, model orchestration, and multi-step reasoning workflows.
• Architect document understanding solutions that transform large volumes of unstructured legal content into structured, searchable, and actionable information.
• Define and optimize retrieval strategies, including semantic search, lexical search, vector databases, reranking models, and hybrid retrieval frameworks.
• Establish evaluation methodologies, benchmarking programs, and quality metrics to measure model performance across both offline testing and production environments.
• Lead the design of human-in-the-loop workflows that improve decision-making, transparency, and AI-assisted legal research experiences.
• Partner with engineering teams to operationalize research findings and transition experimental models into scalable production solutions.
• Provide technical leadership and mentorship to data scientists, helping establish standards, best practices, and innovation frameworks across the organization.
• Influence product strategy by framing complex customer problems, identifying opportunities for AI-driven differentiation, and recommending scalable solutions.
• Evaluate emerging technologies, research advancements, foundation models, and AI tooling to guide future investments and product capabilities.
• Communicate technical findings, tradeoffs, risks, and recommendations to executive leadership and cross-functional stakeholders.

Required Qualifications

• Master's or Ph.D. in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, or a related quantitative field.
• 8+ years of experience in data science, machine learning, artificial intelligence, or applied research roles, with demonstrated technical leadership responsibilities.
• Deep expertise in machine learning, natural language processing, information retrieval, and large-scale text analytics.
• Hands-on experience developing and deploying LLM-powered applications, including RAG pipelines, prompt engineering frameworks, and generative AI solutions.
• Proven track record designing and executing experimentation frameworks, model evaluations, benchmarking programs, and performance measurement strategies.
• Experience building document intelligence solutions involving classification, entity extraction, document segmentation, semantic understanding, and knowledge extraction.
• Expertise in retrieval systems, vector search, embeddings, ranking algorithms, hybrid search architectures, and relevance optimization.
• Experience designing agentic AI workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar orchestration technologies.
• Strong proficiency with Python and modern AI/ML frameworks, including PyTorch, TensorFlow, Hugging Face, OpenAI APIs, or equivalent technologies.
• Strong foundation in statistics, predictive modeling, experimentation, and applied research methodologies.
• Experience collaborating with engineering teams to scale AI solutions into production environments.
• Exceptional problem-framing skills with the ability to transform ambiguous business challenges into structured AI solutions.
• Strong communication and stakeholder management skills with the ability to influence technical and non-technical audiences.

Preferred Qualifications

• Experience working with legal, regulatory, compliance, risk management, or other document-intensive domains.
• Knowledge of knowledge graphs, reasoning systems, and advanced AI evaluation techniques.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience developing AI governance, model monitoring, and responsible AI practices.
• Published research, patents, open-source contributions, or demonstrated thought leadership within AI/ML communities.
• Experience leading cross-functional AI initiatives from concept through production deployment.