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Biotech Data Science Jobs in Raleigh, NC (NOW HIRING)

Lead Data Manager

Durham, NC ยท On-site

$89K - $224K/yr

Minimum 7+ years of Clinical Data Management experience in pharmaceutical, biotechnology, or CRO ... life sciences and healthcare industries. We create intelligent connections to accelerate the ...

Lead Data Manager

Durham, NC ยท On-site

$89K - $224K/yr

Minimum 7+ years of Clinical Data Management experience in pharmaceutical, biotechnology, or CRO ... life sciences and healthcare industries. We create intelligent connections to accelerate the ...

Lead Data Manager

Durham, NC ยท On-site

$89K - $224K/yr

Minimum 7+ years of Clinical Data Management experience in pharmaceutical, biotechnology, or CRO ... life sciences and healthcare industries. We create intelligent connections to accelerate the ...

CMPS) is a biotechnology company dedicated to unlocking urgently needed new treatment options in ... Deliver fair-balanced, scientifically rigorous presentations on clinical data, real-world evidence ...

Strong experience supporting HIV clinical trials and drug development within the pharmaceutical or biotechnology industry. * Advanced degree in Statistics, Computer Science, Data Science, or a ...

Showing results 41-60

Biotech Data Science information

See Raleigh, NC salary details

$36.5K

$119.3K

$191K

How much do biotech data science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for biotech data science in Raleigh, NC is $119,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $132,200.00 per year, depending on experience, location, and employer.

What is a biotech data science?

A Biotech Data Science job involves analyzing complex biological and pharmaceutical data to drive research, innovation, and decision-making. Professionals in this field use machine learning, statistical modeling, and bioinformatics tools to extract insights from genomics, clinical trials, and drug discovery datasets. They collaborate with scientists, engineers, and healthcare professionals to improve treatments, develop new therapies, and optimize bioprocesses. Strong programming skills, domain knowledge in biology or biotechnology, and expertise in data analysis are essential for success in this role.

What are the key skills and qualifications needed to thrive in biotech data science, and why are they important?

To thrive in Biotech Data Science, you need a solid background in biology or biotechnology, strong statistical and analytical skills, and experience with data analysis languages like Python or R. Familiarity with bioinformatics tools, sequencing platforms, and data visualization software is often expected, with certifications in data science or related fields considered a plus. Excellent problem-solving, communication, and collaboration skills are essential when working across multidisciplinary teams. These competencies enable effective interpretation of complex biological data, driving innovation and insights in the biotech industry.

What are the most common challenges faced by professionals in biotech data science roles?

One of the primary challenges in Biotech Data Science is working with large, complex, and sometimes incomplete biological datasets, which require advanced analytical approaches and careful data curation. Professionals often need to stay current with rapidly evolving technologies and methods, which can be demanding but also rewarding for those who enjoy continuous learning. Collaboration with scientists, engineers, and regulatory teams is common, so adapting communication styles and translating technical findings to diverse audiences is key. Overcoming these challenges leads to meaningful scientific discoveries and significant career growth opportunities.

What are popular job titles related to Biotech Data Science jobs in Raleigh, NC?

For Biotech Data Science jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Biotech Data Science jobs in Raleigh, NC look for?

The top searched job categories for Biotech Data Science jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Biotech Data Science jobs?

Cities near Raleigh, NC with the most Biotech Data Science job openings:

Infographic showing various Biotech Data Science job openings in Raleigh, NC as of August 2026, with employment types broken down into 56% Full Time, 13% Part Time, 10% Temporary, and 21% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $119,312 per year, or $57.4 per hour.

VP, AI Center of Excellence (CoE), Enterprise Systems

Personal Genome Diagnostics (pgdx)

Durham, NC โ€ข On-site

$163K - $210K/yr

Other

This job post hasย expired today.ย Applications are no longer accepted.


Job description

VP, AI Center of Excellence (CoE), Enterprise Systems

Labcorp is seeking a VP, AI Center of Excellence (CoE), Enterprise Systems to join our team in Durham, NC.

Location: Durham, NC. Applicants who live within 35 miles of Durham, NC location will follow a hybrid schedule. This schedule includes a minimum of three in office days per week in Durham, supporting both collaboration and flexibility.

Work Schedule: This is a full-time, exempt (salaried) position assigned to a First Shift schedule, with standard business hours of Monday through Friday, 8:00 a.m. to 5:00 p.m. EST. Business needs may occasionally require flexibility in work hours, including earlier, later, or additional hours, with reasonable notice provided when possible.

Job Responsibilities
  • Provide strategic and operational leadership for the AI Center of Excellence (CoE) within Enterprise Systems.
  • Lead execution of transformational and operational AI initiatives aligned to enterprise and business objectives.
  • Partner with senior business and IT stakeholders to translate business needs into scalable AI solutions.
  • Lead and manage a team of AI Architects and AI Engineers, driving engineering excellence and delivery consistency.
  • Own the end-to-end AI delivery lifecycle, including ideation, intake management, use case identification, evaluation, prioritization, design, development, deployment, and lifecycle management.
  • Establish structured intake, evaluation, and prioritization frameworks aligned to enterprise priorities and business value.
  • Partner with Enterprise AI Architecture and IT teams to ensure alignment with enterprise tools, standards, and best practices.
  • Ensure AI solutions comply with enterprise architecture, security, governance, and technology standards.
  • Oversee architecture, design, and implementation of AI solutions to ensure scalability, performance, and reliability.
  • Coordinate with Project Delivery Managers and Delivery CoE teams to ensure integration of AI and non-AI solution components.
  • Collaborate with development and QA teams on solution components such as UI/UX and data engineering.
  • Build, mentor, and develop high-performing AI teams, including defining performance goals and development plans.
  • Lead talent strategy for AI teams, including recruitment, retention, and career development.
  • Provide executive oversight of vendor relationships across consulting, services, and delivery partners.
  • Manage multiple delivery engagement models, including services-based, outcome-based, and staff augmentation.
  • Ensure vendor-delivered solutions align with enterprise standards, timelines, and expected outcomes.
  • Drive delivery excellence through scalable processes, reuse of AI capabilities, and continuous improvement initiatives.
  • Provide executive reporting, risk management, and issue resolution for AI initiatives.
  • Act as an enterprise AI advocate, driving adoption, change management, and integration of AI into business processes.
Minimum Qualifications
  • High school diploma with 19 or more years of experience in enterprise technology delivery, data, analytics, or AI initiatives; or Associate degree with 17 or more years of experience; or Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a technical field with 15 or more years of experience; or Master's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a technical field with 13 or more years of experience
  • 15 or more years of experience leading enterprise technology delivery initiatives, including data, analytics, or AI programs
  • 5 or more years of experience building and leading teams of AI architects, engineers, or data professionals
  • 10 or more years of experience owning end-to-end solution delivery lifecycles, including ideation, design, development, deployment, and lifecycle management
  • 10 or more years of experience managing vendor relationships and delivering solutions using services-based, outcome-based, or staff augmentation engagement models
Preferred Qualifications
  • Master's degree in Business Administration, Data Science, Artificial Intelligence, or a technical discipline
  • 10 or more years of experience in healthcare, diagnostics, life sciences, or biotechnology environments
  • 5 or more years of experience working with AI or machine learning technologies, including generative AI, natural language processing, or predictive analytics
  • 5 or more years of experience working with enterprise platforms such as AWS, Databricks, Snowflake, or similar cloud and data ecosystems
  • 5 or more years of experience applying responsible AI governance frameworks, ethical AI principles, or regulatory compliance standards
  • 5 or more years of experience collaborating with AI vendors, startups, research institutions, or innovation partners
Additional Job Standards

Strategic and Business Acumen

  • Ability to define and execute enterprise-level strategies aligned with corporate objectives.
  • Understanding of financial and operational drivers to support AI investment prioritization and decision-making.
  • Knowledge of healthcare or life sciences industry dynamics and regulatory environments.

AI and Emerging Technology Expertise

  • Understanding of AI and machine learning concepts, including generative AI, large language models, natural language processing, and predictive analytics.
  • Familiarity with data ecosystems, model lifecycle management, and AI platforms.
  • Awareness of responsible AI principles, explainability, fairness, and compliance considerations.

Leadership and Influence

  • Ability to build relationships with executive stakeholders and influence enterprise decision-making.
  • Experience leading cross-functional teams in matrixed environments.
  • Strong executive communication and storytelling capabilities.

Innovation and Transformation

  • Ability to identify and prioritize high-impact AI use cases.
  • Experience developing business cases, roadmaps, and implementation strategies.
  • Ability to assess feasibility, scalability, and risk of emerging technologies.

Organizational Change and Enablement

  • Experience driving enterprise adoption of new technologies and ways of working.
  • Ability to support organizational transformation and talent development initiatives.
  • Ability to operate in evolving, innovation-driven environments.

External Ecosystem Engagement

  • Understanding of AI vendor landscape, startups, and research ecosystems.
  • Ability to build partnerships that accelerate enterprise AI capabilities.
  • Up to 25% travel may be required.
About the Role

The VP, AI Center of Excellence (CoE), Enterprise Systems is responsible for operationalizing Labcorp's enterprise AI-first strategy and driving the delivery of AI initiatives across Diagnostics, Central Laboratory Services, and Early Development business units. This role owns the end-to-end AI delivery portfolio, partnering with senior business and IT stakeholders to implement scalable AI solutions that deliver measurable business outcomes.

Reporting to the SVP, Enterprise Systems, this position leads AI architecture, delivery, and governance within Enterprise Systems while collaborating closely with Enterprise AI Architecture, Security, Infrastructure, and delivery teams. The role ensures AI solutions align with enterprise standards, drives adoption across the organization, and builds high-performing teams that enable long-term competitive advantage through AI.