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Artificial Intelligence Biotech Manager information

What does an artificial intelligence biotech manager do?

An Artificial Intelligence Biotech Manager oversees the integration of AI technologies into biotechnology research and development projects. They manage teams of scientists, data analysts, and engineers to develop innovative solutions such as drug discovery, genomics analysis, or personalized medicine using machine learning and other AI tools. Their responsibilities include project management, collaboration with stakeholders, ensuring regulatory compliance, and staying updated with advancements in both AI and biotechnology. The role requires a blend of technical expertise, leadership skills, and strategic vision.

What are the key skills and qualifications needed to thrive as an artificial intelligence biotech manager?

To thrive as an Artificial Intelligence Biotech Manager, you need a strong background in biotechnology, data science, and AI, often supported by an advanced degree in a relevant field and experience in both biotech and AI project management. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), bioinformatics tools, and regulatory compliance systems is typically required. Exceptional leadership, strategic thinking, and cross-disciplinary communication skills help you effectively bridge the gap between technical teams and life sciences stakeholders. These competencies are crucial for driving innovation, ensuring regulatory compliance, and delivering impactful AI-driven solutions in the biotech sector.

How does an artificial intelligence biotech manager typically collaborate with cross-functional teams in the development of new biotech solutions?

An Artificial Intelligence Biotech Manager works closely with interdisciplinary teams, including data scientists, bioinformaticians, laboratory researchers, and regulatory experts. They coordinate project timelines, ensure clear communication of goals, and facilitate the integration of AI-driven approaches into biotech research. Regular meetings and collaborative platforms are often used to align priorities, troubleshoot challenges, and track progress. This role requires strong leadership and the ability to translate technical AI concepts into actionable strategies for the biotech team.

What is the difference between Artificial Intelligence Biotech Manager vs Data Scientist?

AspectArtificial Intelligence Biotech ManagerData Scientist
Required CredentialsAdvanced degree in biotech, AI, or related fields; experience in biotech and AI projectsDegree in computer science, statistics, or related fields; proficiency in programming and data analysis
Work EnvironmentBiotech companies, research labs, biotech startupsTech firms, research institutions, healthcare organizations
Employer & Industry UsageBiotech and pharmaceutical industries integrating AI solutionsVarious industries including tech, finance, healthcare, and research

While both roles involve data and AI, the Artificial Intelligence Biotech Manager focuses on leading AI projects within biotech companies, combining biotech expertise with AI management. Data Scientists primarily analyze data and develop models across diverse industries. The manager role emphasizes leadership and industry-specific knowledge, whereas Data Scientists focus on technical data analysis skills.

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Infographic showing various Artificial Intelligence Biotech Manager job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 80% Physical, 2% Hybrid, and 18% Remote job distribution.

Artificial Intelligence SME

Washington, DC

Tunnell Government Services
See more jobs at Tunnell Government Servicesexternal

Full-time

Re-posted yesterday

Job description

Artificial Intelligence SME
A Subject Matter Expert (SME) in artificial intelligence with a focus on healthcare and biomedical research is needed to provide contracted support to the Biomedical Advanced Research and Development Authority (BARDA), within the U.S. Department of Health and Human Services (HHS) in Washington, DC. The mission of BARDA is to develop and procure medical countermeasures (MCM) that address the public health and medical consequences of chemical, biological, radiological, and nuclear (CBRN) accidents, incidents and attacks, pandemic influenza, and emerging infectious diseases. Specifically, BARDA supports the advanced development and procurement of drugs, vaccines and other products that are considered priorities for national health security. For more information on BARDA please visit their website at: http://www.phe.gov/about/BARDA/Pages/default.aspx
Specifically, this individual will provide strategic, technical, and scientific expertise on the application of artificial intelligence (AI), machine learning (ML), and advanced data analytics to BARDA's mission of developing and procuring medical countermeasures (MCMs) for public health emergencies. The AI SME will advise leadership, program managers, and technical teams on the integration of AI technologies across BARDA's programs, ensuring the agency remains at the forefront of innovation in biodefense, pandemic preparedness, and health security.

Major Duties & Responsibilities:

  • Advise BARDA leadership on emerging trends, opportunities, and risks in AI and related technologies for vaccines and/or therapeutics development.
  • Provide subject matter expertise to BARDA divisions in evaluating AI-enabled technologies, tools, and proposals.
  • Assess AI approaches used in diagnostics, therapeutics, and vaccines including review of algorithms and algorithm performance
  • Guide the design, implementation, and validation of AI applications to ensure scientific rigor, transparency, and compliance with federal policies.
  • Contribute to the formulation of policies, standards, and ethical frameworks governing AI use within BARDA.
  • Perform expert analysis and provide recommendations for applications of machine learning/artificial intelligence tools and capabilities to field of biotech research and development (e.g. digital health, drug discovery and design, clinical validation).
  • Evaluating diverse data sets for use with AI products/tools, such as EHR, claims, laboratory/clinical data, physiological data, genomic data, viral variant data, and/or social determinants of health data.
  • Advising on improvements to data collection and curation, developing standards, and developing data use and sharing agreements to enable AI applications
  • Advising R&D partnerships developing artificial intelligence products/tools to improve model function, design clinical validation studies, and implement production deployment and maintenance processes.


Requirements:

  • Advanced degree (Ph.D. or M.S) in Computer Science, Data Science, Engineering, Bioinformatics, or a related field
  • 15+ years of experience in vaccines and/or therapeutics development
  • Minimum of 8-10 years of experience applying AI/ML in healthcare, biomedical research, or health security contexts
  • Demonstrated expertise in algorithm development, data modeling, and AI governance
  • Demonstrated ability to communicate complex AI concepts to diverse stakeholders
  • Demonstrated experience serving as technical expert and leader in machine learning/artificial intelligence, data analytics, and algorithm development using medical and/or biological data.
  • Demonstrated understanding of software development principles and cloud-based platforms and services relevant to AI development.
  • Expertise in understanding artificial intelligence model function, clinical validation, production deployment, and ongoing maintenance

Must be a US Citizen or Full Green Card holder.

Apply