Would you like to lead a team building production-grade NLP and LLM capabilities that transform legal and business information into actionable intelligence?
Do you enjoy shaping the future of AI and data science in a way that delivers measurable customer and business impact?
** Please note that the selected individual for this role will be expected to work in our Raleigh, NC location from the time of joining. If you reside outside of the Raleigh region and you are unable or unwilling to relocate, then please consider other roles across our organization that might allow for remote locations. **Role Overview: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.
Key Responsibilities:Scope & Impact- 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
Technical & Product Leadership:- 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
Team & Operational Excellence:- Mentor and grow a multidisciplinary team of LLM-focused Data Scientists and ML Engineers.
- Drive cross-functional collaboration with Legal SMEs, Data Engineers, Product Managers, and Design.
- Establish best practices for evaluation, observability, and responsible use of generative AI.
- Oversee development of infrastructure to support continuous delivery and monitoring of LLM systems in production environments.
Core Qualifications:Experience & Education- 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
- Typically requires:
- 8+ years of relevant experience in data science, machine learning, or applied AI
- 4+ 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 influence
- Acting as a change agent, embedding best practices into workflows and systems
- Driving both team development and strategic outcomes across a broad scope
- Ability 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.
Work in a way that works for you:We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
- Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive
Working for you:We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
- 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
#AIFluency
U.S. National Base Pay Range: $118,300 - $219,800. Geographic differentials may apply in some locations to better reflect local market rates.
This job is eligible for an annual incentive bonus.
