Responsibilities

• Set the vision and strategic priorities, acting as a recognized expert for Data Science
• Lead and develop a team of data scientists and ML engineers, setting the cultural tone for the group
• Drive applied research with a clear path to production, explicitly balancing innovation against real-world constraints including latency, cost, and reliability
• Build and scale evaluation science capabilities within the team, including offline evaluation frameworks, automated benchmarking pipelines, and human-in-the-loop feedback systems to rigorously measure model quality and business impact
• Champion hands-on rapid prototyping and iteration
• Collaborate with other Data Science teams to maximize re-use of components and patterns, eliminating waste, duplication and unnecessary customization
• Operate with broad scope, coordinating across multiple cross-functional teams, systems, and domains
• Collaborate closely with other Data Science teams, to define and execute the AI roadmap across the content lifecycle, maximizing reuse in areas including: Content collection (e.g. “web scraping”) and transformation; Metadata extraction, enrichment, and classification; Agentic workflows turning real-world events and legal content into legal intelligence; AI-powered downstream product capabilities
• Design and deploy scalable, production-grade AI systems, including: LLM-powered document understanding and generation; Agentic workflows balancing agent autonomy and efficiency with required structure and accuracy; Retrieval-augmented generation (RAG) pipelines; Hybrid ML + rules-based systems for structured content
• Lead through execution and by example: Actively writing code, not just delegating; Building and demoing working prototypes (e.g. by “vibe coding”); Directly contributing to experiments and production models

Requirements

• Advanced degree (Master’s or PhD) in Data Science, Computer Science, Statistics, or a related field strongly preferred, or equivalent practical experience
• Bachelor’s degree in a relevant field with significant applied experience in data science, machine learning, or AI
• 8+ years of relevant experience in data science, machine learning, or applied AI
• 4+ years of leadership experience (direct or indirect team management)
• Proficient with Python, ML and LLM tooling such as Google ADK, LangChain, ML Frameworks (e.g. TensorFlow, PyTorch) and prompt tuning techniques
• Familiarity with vector databases, knowledge graphs, and hybrid retrieval architecture
• Strong experience working with structured and unstructured data at scale
• Ability to design and implement data pipelines and preparation workflows
• Experience integrating ML into complex, multi-stage processing systems
• Working knowledge of containerization, CI/CD, RESTful API Design and model serving tools

Preferred

• Graduate degree in Computer Science, AI, Machine Learning, or equivalent experience
• 8+ years of post-degree experience, with 4+ years in a data science or applied AI leadership role, with a focus on NLP/LLM systems
• Prior experience in legal tech, legal AI, or document-intensive domains is highly desirable
• Familiarity with ethical/legal considerations in deploying generative AI in professional settings

Benefits

• Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
• Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
• Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs
• Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
• Family Benefits, including bonding and family care leaves, adoption, and surrogacy benefits
• Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
• Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice