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Scientific Director Jobs in Raleigh, NC (NOW HIRING)

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 ...

Director, HEOR. Roles and responsibilities ( Include but are not limited to ): External Scientific Engagement * Identify, cultivate, and maintain peer-to-peer relationships with key payer thought ...

We're uniting science, technology, and talent to get ahead of disease together. Are you energized ... As a Director, Medical Science Liaison, you will lead the performance of the MSL team by setting ...

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Scientific Director information

See Raleigh, NC salary details

$89.4K

$152.3K

$188.1K

How much do scientific director jobs pay per year?

As of Aug 12, 2026, the average yearly pay for scientific director in Raleigh, NC is $152,338.00, according to ZipRecruiter salary data. Most workers in this role earn between $145,300.00 and $164,800.00 per year, depending on experience, location, and employer.

What is the difference between Scientific Director vs Research Scientist?

AspectScientific DirectorResearch Scientist
Required credentialsAdvanced degrees (PhD or MD), extensive research experienceTypically a PhD or Master's degree in a relevant field
Work environmentLeadership roles in labs, research institutions, or pharmaceutical companiesLaboratory or field research settings, often under supervision
Employer and industry usageUsed in biotech, pharma, academia for overseeing research programsCommon in research labs, academia, and industry for conducting experiments

The main difference is that a Scientific Director oversees research programs and manages teams, requiring leadership skills and strategic planning, while a Research Scientist focuses on conducting experiments and generating data. Both roles require advanced degrees, but the Scientific Director has broader responsibilities in guiding research direction.

How does a scientific director typically collaborate with cross-functional teams in a research organization?

Scientific Directors play a central role in coordinating efforts across various departments, such as research scientists, clinical teams, regulatory affairs, and business development. They facilitate communication to ensure that scientific objectives align with organizational goals and project timelines. Regular meetings, joint project planning, and shared data platforms are commonly used to maintain transparency and drive progress. This collaborative approach helps streamline decision-making and fosters innovation by integrating diverse expertise.

What is a scientific director?

A Scientific Director is a senior leader responsible for overseeing and guiding the scientific research and development efforts within an organization. They set the strategic direction for research programs, manage scientific teams, and ensure projects align with the organization’s goals and regulatory standards. Scientific Directors often collaborate with other departments, secure funding, and represent the organization at conferences or in partnerships. Their role is crucial in driving innovation and maintaining the quality and integrity of scientific work.

What does a scientific director do?

A scientific director manages research programs for a company, organization, or institution. Your job duties can vary depending on where you work, but as a scientific director, you help define the research direction of an organization. You may oversee laboratory experiments, hire researchers to meet staffing needs, and offer guidance so that the research meets specific goals. You establish initiatives and create strategies that help your facility meet particular objectives. A scientific director sometimes acts as a liaison between researchers and other executives or administrators.

What are the key skills and qualifications needed to thrive as a scientific director, and why are they important?

To thrive as a Scientific Director, you need advanced expertise in scientific research, typically supported by a Ph.D. and significant leadership experience in your field. Proficiency with research management tools, data analysis software, and familiarity with regulatory compliance systems is expected. Strong strategic thinking, communication, and team leadership skills set exceptional candidates apart. These skills are vital for driving innovative research, managing multidisciplinary teams, and ensuring project success within organizational and regulatory frameworks.
What are the most commonly searched types of Scientific jobs in Raleigh, NC? The most popular types of Scientific jobs in Raleigh, NC are:
What are popular job titles related to Scientific Director jobs in Raleigh, NC? For Scientific Director jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Scientific Director jobs in Raleigh, NC look for? The top searched job categories for Scientific Director jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Scientific Director jobs? Cities near Raleigh, NC with the most Scientific Director job openings:
Infographic showing various Scientific Director job openings in Raleigh, NC as of August 2026, with employment types broken down into 69% Full Time, 27% Part Time, and 4% Temporary. Highlights an 83% In-person, 4% Hybrid, and 13% Remote job distribution, with an average salary of $152,338 per year, or $73.2 per hour.

Director, Data Sciences

LexisNexis

Raleigh, NC • On-site

Full-time

Re-posted 27 days ago


LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

188th of 488 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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