Sr. Manager Data Science - Gen AI and Content Systems

About the role

We are seeking a hands-on Senior Manager of Data Science to lead a high-impact team in developing the strategy, standards, and execution of AI across our content ecosystem. You will lead a team that embeds machine learning and generative AI directly into production systems operating at scale. Our applied research opportunity balances innovation with practical constraints (e.g. latency, cost, reliability), requiring a strong ability to quickly iterate on prototypes (e.g. "vibe coding"), communicate tradeoffs, and rapidly deploy to production environments. This role is central to our transformation toward an intelligent, agent-enabled content platform which is capable of grounded reasoning, turning structured and unstructured data sources into legal knowledge.

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
• Establish and scale best practices in Data Science, including:
• Model development, evaluation, and monitoring
• Prompt engineering and experimentation frameworks
• Data preparation and feature engineering standards
• Reusable components and platform capabilities
• Partner closely with engineering, architecture, and product leaders to:
• Integrate AI into large-scale distributed systems
• Ensure performance, scalability, and reliability
• Align technical solutions with business outcomes
• Translate complex, ambiguous problems into clear project plans and executable solutions, and lead teams through delivery
• Present tradeoffs, alternative approaches and options when faced with delivery constraints

Qualifications

• 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 AITypically requires:8+ years of relevant experience in data science, machine learning, or applied AI4+ years of leadership experience (direct or indirect team management)
• We recognize that exceptional candidates may follow non-traditional paths and value demonstrated impact, technical depth, and leadership over strict credential requirements.
• Success in this role requires leading through both technical expertise and organizational influenceActing as a change agent, embedding best practices into workflows and systemsDriving both team development and strategic outcomes across a broad scopeAbility to select the right tools and technologies to solve business problems
• Technical Proficiency 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.Cloud infrastructure experience on AWS (preferred), Azure, or GCP.Familiarity with AI Coding Tools (e.g. GitHub CoPilot, Claude Code, OpenAI Codex)
• Preferred Background 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.