Director, Data Sciences

LexisNexis•Raleigh, NC

1d•Onsite

About The Position

LexisNexis Legal & Professional, serving customers in over 150 countries with 11,800 employees worldwide, is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. Our company is a leader in deploying AI and advanced technologies to improve productivity and transform the legal market. We prioritize using the best models from today's top creators for each legal use case. The Director, Data Sciences raises data-driven decision making of a function within a business unit through team leadership. They are also client/industry-facing, and they evangelize methodologies and best practices. They lead people and teams to develop an overall strategy for the execution of projects including creating use cases, roadmaps, alignment of stakeholders, and prioritization. This person acts as coach and leader of Managers and Data Scientists, as well as other resources. Influence should extend outside the director's immediate team to other teams within the director's peers. The Director drives development and implementation across the team to the business, rooted in a deep understanding of our customers, markets, trends, and challenges.

Requirements

Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.
10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.
Demonstrated experience in managing and scaling data science teams of 15+ professionals.
Proven record of delivering high-impact AI and ML solutions that have driven significant business value.
Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.
Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.
Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.
Strong business acumen with the ability to translate complex technical concepts into business value.
Excellent communication and leadership skills, with experience presenting to executive leadership.
Experience working in a global or multicultural environment
Record of successful collaboration with product, engineering, and business teams.
Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.

Responsibilities

Strategic Leadership : Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.
Team Management : Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.
Advanced Research Direction : Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage. Champion innovation by staying current with the latest trends and techniques in data science and allocating resources to promising new approaches.
Machine Learning and AI Solutions : Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems.
Data Analysis and Modeling : Oversee advanced data analysis, modeling, and machine learning to develop predictive and prescriptive models that drive business outcomes.
Data Collection and Preparation : Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.
Data Visualization Strategy : Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.
Cross-functional Collaboration : Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.
Model Deployment and MLOps : Oversee the deployment of machine learning models into production environments, ensuring scalability and reliability.
Documentation Standards : Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.
Stakeholder Management : Communicate the value and impact of data science initiatives to C-suite executives and business stakeholders.
Budget and Resource Management : Manage departmental budget, resource allocation, and infrastructure needs for data science operations.
Ethical AI Governance : Develop and enforce ethical guidelines and best practices for AI development and deployment.

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
In addition to annual Paid Time Off, we offer up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice

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