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Biology Data Science Jobs (NOW HIRING)

The ideal candidate has preferred advanced education at the master's or doctoral level in science, engineering, or a related field, along with experience preparing biological data for AI models ...

The ideal candidate has preferred advanced education at the master's or doctoral level in science, engineering, or a related field, along with experience preparing biological data for AI models ...

The Oncology Data Science group within Biomedical Research supports the Oncology Disease Area with computational biology, Artificial Intelligence / Machine Learning (AI/ML), and data engineering for ...

The ideal candidate has preferred advanced education at the master's or doctoral level in science, engineering, or a related field, along with experience preparing biological data for AI models ...

The ideal candidate has preferred advanced education at the master's or doctoral level in science, engineering, or a related field, along with experience preparing biological data for AI models ...

$194K - $305K/yr

Extensive experience applying computational methods in cancer biology.Extensive experience and ... Science, Genomic Data Analysis, Machine Learning (ML), Multimodal, Multimodal Analysis ...

$194K - $305K/yr

Experience in applying computational methods in cancer biology.Demonstrated expertise in the ... in scientific computation environments with adoption of best practices for reproducible data ...

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Biology Data Science information

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$37.5K

$122.7K

$196.5K

How much do biology data science jobs pay per year?

As of Aug 12, 2026, the average yearly pay for biology data science 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.

Can I get into data science with a biology degree?

Biology degrees can provide a strong foundation for data science roles, especially when combined with skills in programming, statistics, and data analysis tools like Python or R. Many data scientists have diverse academic backgrounds, and additional training or certifications in data science can improve job prospects.

What is a biology data science?

A Biology Data Science job involves applying data analysis, machine learning, and computational techniques to biological data. Professionals in this field work with large datasets from genomics, proteomics, ecology, or clinical studies to extract insights and drive scientific discoveries. They often use programming languages like Python or R, along with statistical and bioinformatics tools, to analyze complex biological systems. These roles exist in academia, pharmaceuticals, biotechnology, and healthcare.

What skills and qualifications are needed to thrive as a biology data science?

To excel in Biology Data Science, a strong background in biological sciences paired with expertise in statistical analysis, programming (commonly Python or R), and data interpretation is essential. Familiarity with tools such as bioinformatics platforms, machine learning libraries, and data visualization software, along with relevant certifications in data science or computational biology, is highly valuable. Strong problem-solving skills, attention to detail, and effective communication abilities help you collaborate with multidisciplinary teams and present complex findings clearly. These competencies allow professionals to manage and analyze large biological datasets, driving data-driven discoveries and innovation in research or industry settings.

What are the day-to-day responsibilities of a biology data science?

Professionals in Biology Data Science typically spend their days acquiring, cleaning, and analyzing large sets of biological data, such as genomic sequences or clinical trial results. They use coding and statistical methods to uncover patterns, develop predictive models, and generate insights to support scientific discoveries or healthcare decisions. Collaboration is frequent, often requiring close coordination with biologists, clinicians, and software engineers to interpret data and ensure research objectives are met. Additionally, clear and concise reporting of findings, often through visualizations or presentations, is a regular part of the job. This blend of data science and biology offers dynamic workdays that can have a direct impact on advancing scientific knowledge and improving patient outcomes.

What do biology data scientists do?

Biology data scientists analyze biological data using statistical methods, machine learning, and programming tools like Python or R. They work on projects such as genomics, drug discovery, and ecological modeling to extract meaningful insights from complex datasets.
More about Biology Data Science jobs
What cities are hiring for Biology Data Science jobs? Cities with the most Biology Data Science job openings:
What are the most commonly searched types of Biology Data Science jobs? The most popular types of Biology Data Science jobs are:
What states have the most Biology Data Science jobs? States with the most job openings for Biology Data Science jobs include:
Infographic showing various Biology Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Senior Data Scientist

MD Anderson

Houston, TX • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 170 frontline employees who took The Breakroom Quiz

23rd of 887 rated healthcare providers


Job description

The Senior Data Scientist within the Institute for Data Science in Oncology collaborates with internal and external stakeholders to drive innovation, expand funding opportunities, support research infrastructure, and accelerate the adoption of data science solutions that improve cancer outcomes. The ideal candidate has preferred advanced education at the master's or doctoral level in science, engineering, or a related field, along with experience preparing biological data for AI models, writing successful academic proposals, and supporting translational research studies that advance the adoption of data science, artificial intelligence, machine learning, analytics, or computational tools within healthcare or clinical environments. Minimum $123,000 - Midpoint $154,000 - Maximum $185,000 Work Schedule: Hybrid Onsite/Remote work schedule Why Us.

At UT MD Anderson, this role provides the opportunity to advance transformative cancer data science initiatives, contribute to innovative research programs, develop groundbreaking computational methods, and collaborate with multidisciplinary experts. The position supports professional growth through involvement in high-impact research, grant development, software innovation, and translational science projects while offering flexible hybrid work arrangements and comprehensive benefits. Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance.

Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options. Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups. Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.

Responsibilities Research, Innovation & Method Development Design and develop computational methods for advanced research and development in machine learning, AI, numerical analysis, mathematical modeling, and data processing techniques Advance the frontiers of cancer data science through development and support of novel methods aligned with IDSO Focus Areas Provide technical and data science method development for image analysis, data analysis, AI, machine learning, software development, and prototype implementation Design, analyze, develop, and support formulas, algorithms, and software for complex scientific and mathematical applications Lead research and data science projects under the direction of IDSO directors and co-leads Grant Development & Resource Expansion Develop written proposals to secure funding and expand resources available for cancer data science innovations Enable advancement of IDSO priorities through development of grant proposals and funding submissions Support all IDSO programs, including focus areas, fellowships, affiliates, and collaborative initiatives, through proposal development and writing Support JCCO pilot collaborative projects to advance funding opportunities in partnership with IDSO leadership and affiliates Software, Platforms & Infrastructure Contribute to the design, development, integration, and support of ecosystem software applications and data science platforms Strengthen the UT MD Anderson data science ecosystem through software and platform development initiatives Drive integration of focus area technical advances into research and clinical infrastructure Develop methods for integrating internal and external computational models into institutional research and clinical environments Collaboration & Translational Research Foster team-based data science approaches and study designs that advance clinical adoption of data science methodologies Support community development, collaboration initiatives, and multidisciplinary partnerships across research programs Work with IDSO directors and co-leads to envision new concepts and deliver transformative data science projects Design and support translational efforts that accelerate the use of computational tools in healthcare settings Stakeholder Engagement Collaborate with internal partners and external academic and industry organizations to improve data science infrastructure and platforms Communicate technical concepts and project outcomes to a variety of stakeholder groups Support strategic initiatives that improve ecosystem capabilities and resource availability Perform other duties as assigned EDUCATION Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. Preferred: Master's Degree Science, Engineering or related field. Preferred: PhD Science, Engineering or related field.

WORK EXPERIENCE Required: 5 years Experience in scientific software or industry programming with a concentration in scientific computing. or Required: 3 years Required experience with Master's degree. or Required: 1 year Required experience with PhD.

Preferred: Experience preparing data for and creating AI models for biological applications, experience writing successful academic proposals, experience designing & or supporting translational research studies that advanced the adoption of data science, AI/ML, analytics, or computational tools in clinical or healthcare environment. Work Schedule: Hybrid Onsite/Remote Schedule The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition. This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening

The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html Additional Information Requisition ID: 182148 Employment Status: Full-Time Employee Status: Regular Work Week: Days Minimum Salary: US Dollar (USD) 123,000 Midpoint Salary: US Dollar (USD) 154,000 Maximum Salary : US Dollar (USD) 185,000 FLSA: exempt and not eligible for overtime pay Fund Type: Hard Work Location: Hybrid Onsite/Remote Pivotal Position: Yes Referral Bonus Available?: Yes Relocation Assistance Available?: Yes #LI-Hybrid Apply


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