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Director Machine Learning Jobs in Raleigh, NC (NOW HIRING)

The Director, Data Sciences is responsible for leading a team of data scientists and developing ... Oversee advanced data analysis, modeling, and machine learning to develop predictive and ...

The Director, Data Sciences is responsible for raising data-driven decision making within a ... Oversee advanced data analysis, modeling, and machine learning to develop predictive and ...

Director, GenAI Technology

Durham, NC · On-site

$126K/yr

  • Medical

  • Retirement

  • PTO

In this role, the individual leads machine learning projects with diverse scope and complex business and technical challenges. Coordinates with senior business and technology partners to develop ...

... machine learning best practices. • Working with product leaders to apply data science solutions. • Leading small- to medium-sized teams (direct or indirect). Qualifications : Required : • ...

... machine learning best practices. • Working with product leaders to apply data science solutions. • Leading small- to medium-sized teams (direct or indirect). Qualifications : Required : • ...

Senior Data Scientist

Durham, NC · On-site

$90 - $120/hr

... machine learning, business strategy, and the modern data platform (Microsoft Fabric, OneLake, and Azure), this role designs, builds, and deploys predictive models that have direct revenue impact ...

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Director Machine Learning information

See Raleigh, NC salary details

$35K

$89.4K

$137.1K

How much do director machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for director machine learning in Raleigh, NC is $89,361.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,500.00 and $103,000.00 per year, depending on experience, location, and employer.

What is a director machine learning?

A Director of Machine Learning leads teams in developing and deploying machine learning models to solve business challenges. They define the AI strategy, oversee research, and ensure models are scalable and ethical. This role requires expertise in machine learning, data science, and leadership, as well as collaboration with cross-functional teams. Directors also stay updated on industry advancements and drive innovation within their organizations.

What are the primary responsibilities and challenges faced by a director machine learning on a daily basis?

A Director of Machine Learning is typically responsible for overseeing the development and deployment of machine learning solutions, mentoring technical teams, setting strategic direction for AI initiatives, and ensuring the alignment of projects with organizational goals. Challenges often include balancing innovative research with business priorities, navigating evolving technology landscapes, and coordinating efforts across data science, engineering, and stakeholder teams. This role requires regular collaboration with product managers, executives, and cross-functional departments to prioritize initiatives and communicate complex technical concepts. Successful directors excel at fostering a culture of continuous learning, optimizing team productivity, and staying ahead in a fast-paced, rapidly changing field.

What are the key skills and qualifications needed to thrive in the director machine learning position, and why are they important?

To thrive as a Director Machine Learning, you need advanced expertise in machine learning, statistics, data science, and leadership, typically supported by a master's or Ph.D. in a related field and several years of relevant industry experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and data management systems, as well as certifications like AWS Certified Machine Learning or Google Professional Machine Learning Engineer, are commonly required. Exceptional communication, strategic thinking, and team management skills distinguish top candidates in this role. These capabilities are essential for driving organizational AI initiatives, fostering high-performing teams, and delivering impactful business solutions.

Is a machine learning director a high paying job?

A machine learning director typically earns a high salary due to the specialized skills, leadership responsibilities, and experience required for the role. Compensation often includes base salary, bonuses, and stock options, reflecting the demand for expertise in AI and data science. Salaries can vary based on industry, company size, and location, but generally rank among the higher-paying technology leadership positions.

What does a director of machine learning do?

A director of machine learning oversees the development and implementation of machine learning strategies and projects within an organization. They lead teams of data scientists and engineers, set technical goals, ensure project alignment with business objectives, and often collaborate with other departments to integrate AI solutions using tools like Python, TensorFlow, or PyTorch.

What are the most commonly searched types of Machine Learning jobs in Raleigh, NC?

The most popular types of Machine Learning jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Director Machine Learning jobs?

Cities near Raleigh, NC with the most Director Machine Learning job openings:

Infographic showing various Director Machine Learning job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $89,361 per year, or $43 per hour.

Director, Data Sciences

LexisNexis

Raleigh, NC • On-site

Full-time

Re-posted 4 days ago


LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

189th of 492 rated business services


Job description

Job Summary:
LexisNexis is a global provider of information-based analytics and decision tools for professional and business customers. The Director, Data Sciences is responsible for leading a team of data scientists and developing strategies for data-driven decision making, while overseeing advanced research and the implementation of machine learning solutions.
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.
Qualifications:
Required:
• 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.
Company:
LexisNexis is a data analytics company that provides information solutions and law legal databases to Law and corporate businesses. It is a sub-organization of RELX. Founded in 1970, the company is headquartered in Albany, USA, with a team of 10001+ employees. The company is currently Late Stage.

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