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Manager Biomedical Data Scientist Jobs (NOW HIRING)

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

Connect biomedical sensor data with medical, health, and fitness outcomes * Research and ... Collaborate with an interdisciplinary team of scientists, engineers, mathematicians for quick ...

NLM Data Scientist

Bethesda, MD · On-site

$100K - $115K/yr

Data Scientist Lexical Intelligence provides software and services related to processing large-scale biomedical information sources. Our Natural Language Processing (NLP) and analytics software is ...

Data Scientist Lexical Intelligence provides software and services related to processing large-scale biomedical information sources. Our Natural Language Processing (NLP) and analytics software is ...

Provide input to biomedical research scientist presentations and publications regarding rigorous and appropriate analytic approaches. * Lead complex data presentation to technical and non-technical ...

Provide input to biomedical research scientist presentations and publications regarding rigorous and appropriate analytic approaches. * Lead complex data presentation to technical and non-technical ...

Provide input to biomedical research scientist presentations and publications regarding rigorous and appropriate analytic approaches. * Lead complex data presentation to technical and non-technical ...

Curate and extend ontologies for clear mapping into established biomedical ontologies and ... Draft and manage documentation, such as data dictionaries, data lineage, and data flow diagrams, to ...

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Manager Biomedical Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do manager biomedical data scientist jobs pay per year?

As of Sep 10, 2026, the average yearly pay for manager biomedical data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a manager biomedical data scientist?

Manager Biomedical Data Scientists are professionals who oversee teams of data scientists and analysts working with biomedical data. They are responsible for directing research projects, managing data workflows, and ensuring the integrity and security of sensitive health information. In addition, they collaborate with clinicians, researchers, and IT professionals to develop data-driven solutions that improve healthcare outcomes. Their role combines technical expertise in data science and bioinformatics with leadership and project management skills.

How does a manager biomedical data scientist typically collaborate with cross-functional teams in a healthcare or research setting?

A Manager Biomedical Data Scientist works closely with a variety of professionals, including clinicians, laboratory scientists, software engineers, and regulatory specialists. Their role often involves translating complex biomedical data into actionable insights for both technical and non-technical stakeholders. They lead data science teams, coordinate project timelines, and ensure that data-driven solutions align with organizational goals. Effective communication and the ability to bridge gaps between research and practical application are essential for success in this collaborative environment.

What are the key skills and qualifications needed to thrive as a manager biomedical data scientist, and why are they important?

To thrive as a Manager Biomedical Data Scientist, you need advanced knowledge of biostatistics, machine learning, data analysis, and a graduate degree in a relevant field such as bioinformatics or computational biology. Expertise in tools like Python, R, SQL, and platforms such as cloud computing, as well as experience with regulatory standards and data privacy, is typically required. Strong leadership, project management, and communication skills help drive team performance and facilitate collaboration across interdisciplinary groups. These skills ensure the effective translation of complex biomedical data into actionable insights that enhance research and clinical outcomes.

What is the difference between Manager Biomedical Data Scientist vs Biomedical Data Scientist?

AspectManager Biomedical Data ScientistBiomedical Data Scientist
Required CredentialsMaster's or PhD in Bioinformatics, Data Science, or related field; experience in team leadershipMaster's or PhD in Bioinformatics, Data Science, or related field; focus on technical skills
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersPerforms data analysis, develops models, supports research teams
Employer & Industry UsagePharmaceutical companies, biotech firms, healthcare organizationsResearch institutions, biotech companies, healthcare providers

The main difference is that a Manager Biomedical Data Scientist oversees teams and projects, while a Biomedical Data Scientist primarily focuses on data analysis and model development. The managerial role involves leadership responsibilities, whereas the data scientist role emphasizes technical expertise.

What cities are hiring for Manager Biomedical Data Scientist jobs?

Cities with the most Manager Biomedical Data Scientist job openings:

What are the most commonly searched types of Biomedical Data Scientist jobs?

The most popular types of Biomedical Data Scientist jobs are:

What states have the most Manager Biomedical Data Scientist jobs?

States with the most job openings for Manager Biomedical Data Scientist jobs include:

What are popular job titles related to Manager Biomedical Data Scientist jobs?

For Manager Biomedical Data Scientist jobs, the most frequently searched job titles are:

88-50100571 Analytical Data Scientist

San Jose, CA • On-site

$142K - $197K/yr

Full-time

Re-posted 7 days ago


Job description

The Position
Genentech, Inc. seeks an Analytical Data Scientist at its South San Francisco, California location.
Duties: Within global biotechnology organization, conduct statistical programming and analyses to support the company's Product Development Data (PDD) Sciences used for pharmaceutical and biotech drug development. Lead statistical programming teams in planning, designing, and implementing statistical software solutions for clinical trial reporting and analysis. Assess, clarify and make statistical recommendations on study requirements, develop statistical programming strategies, and ensure efficient implementation as the Study Lead. Develop data science strategies to meet study and project requirements; manage output specifications and output risk assessments; and specify, review, and implement analysis datasets. Identify and assign deliverables for clinical study team members in support of across molecule programs. Conduct statistical programming and analytics as a component of clinical projects. Communicate with stakeholders from different scientific backgrounds and areas of expertise to negotiate timelines and scope of deliverables. Develop and validate datasets and statistical outputs for clinical studies, including Study Data Tabulation Model (SDTM) datasets, Analysis Data Model (ADaM) datasets, and tables, listings, and figures (TLFs) through adherence to risk assessment and quality control guidelines and internal processes. Assist in developing visualizations/dashboards for data exploration using interactive applications and data insights platforms. Document reproducible and accurate outputs and ensure alignment with programming specifications. Resolve technical issues in code or output that cause data discrepancies. Collaborate with global health authorities to support company's product pipeline and build partnerships to collaborate with global affiliates to support products, processes, and systems while ensuring compliance with regulatory and process requirements.
Education and Experience Requirement: Requires a Master's degree in biostatistics, mathematics, data science or closely related field.
Specials Skills Requirement: Must have the following skills from academic studies, research, or industry: 1) Statistical programming knowledge of clinical and biomedical data in product development processes within biopharmaceutical industry, 2) Software development and programming expertise in SAS, SQL, and R, 3) Statistical methodologies in biomedicine such as survival modeling, causal inference, and clinical trials, and 4) Collaborating with stakeholders from different scientific backgrounds on biomedical related research projects. May telecommute up to 3 days per week.
#LI-DNI #DNI #DE-DNI
Worksite: 1 DNA Way, Central Campus, South San Francisco, California 94080.
The expected annual salary range for this position based on the primary location for this position in South Francisco, California is $142,656 to $197,500 per year. Actual pay within the range will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at
(https://roche.ehr.com/default.ashx?CLASSNAME=splash).
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.