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Biostatistics Machine Learning Jobs (NOW HIRING)

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$209K/yr

Position Overview The Sr. Engineer, Machine Learning Operations, with minimal guidance, works independently and with crossfunctional partners-including biostatisticians, bioinformatics scientists, AI ...

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How much do biostatistics machine learning jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for biostatistics machine learning in the United States is $26.35, according to ZipRecruiter salary data. Most workers in this role earn between $21.39 and $27.88 per hour, depending on experience, location, and employer.

What is biostatistics machine learning?

Biostatistics machine learning refers to the application of machine learning techniques to analyze and interpret biological and health-related data. Professionals in this field use statistical models and algorithms to uncover patterns, make predictions, and assist in decision-making in areas such as clinical trials, genomics, epidemiology, and public health. By combining expertise in statistics, biology, and computer science, they help advance medical research and improve healthcare outcomes. This interdisciplinary approach is essential for managing the complexity and scale of modern biomedical data.

What is the difference between Biostatistics Machine Learning vs Data Scientist?

AspectBiostatistics Machine LearningData Scientist
Required CredentialsMaster's or PhD in Biostatistics, Data Science, or related fields; knowledge of statistical methods and machine learningBachelor's or higher in Computer Science, Statistics, or related; strong programming and analytical skills
Work EnvironmentHealthcare, pharmaceutical, or research institutions focusing on health dataTech companies, finance, marketing, and various industries handling large datasets
Employer & Industry UsagePrimarily in healthcare, clinical research, and public health sectorsAcross multiple industries including tech, finance, retail, and consulting

While both roles involve machine learning and data analysis, Biostatistics Machine Learning focuses on health-related data and statistical modeling in medical research, whereas Data Scientists work across diverse industries with broader data applications. The roles share skills but differ in domain expertise and typical work environments.

What are the key skills and qualifications needed to thrive as a Biostatistics Machine Learning professional, and why are they important?

To excel in Biostatistics Machine Learning, you need a solid background in statistics, data analysis, and programming, often supported by an advanced degree in biostatistics, computer science, or a related field. Proficiency in statistical software (such as R or SAS), machine learning frameworks (like TensorFlow or scikit-learn), and data management systems is typically required. Strong problem-solving, critical thinking, and communication skills help you interpret complex data and collaborate effectively with multidisciplinary teams. These skills ensure accurate data-driven insights and innovative solutions in biomedical research and healthcare analytics.

How do biostatistics machine learning professionals typically collaborate with clinical researchers in a healthcare setting?

Biostatistics machine learning professionals often work closely with clinical researchers to design studies, analyze complex datasets, and interpret results. They translate clinical questions into statistical models and help ensure that data collection methods align with analytical goals. Regular communication is key, as they must explain technical findings in accessible language and adapt modeling approaches based on clinical feedback, fostering a collaborative environment that supports evidence-based decision-making.
Infographic showing various Biostatistics Machine Learning job openings in the United States as of May 2026, with employment types broken down into 33% Full Time, 34% Contract, and 33% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $54,803 per year, or $26.3 per hour.
Postdoctoral Fellow - Biostatistics

Postdoctoral Fellow - Biostatistics

MD Anderson Cancer Center

Houston, TX • On-site

$64K - $76K/yr

Full-time

Medical, Dental, Retirement, PTO

Posted 9 hours ago

MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 164 frontline employees who took The Breakroom Quiz

33rd of 869 rated healthcare providers

Job description

The Department of Biostatistics at The University of Texas MD Anderson Cancer Center is seeking a postdoctoral fellow in biostatistical methodology. This position emphasizes methodological research and publication. The successful candidate will work under the joint supervision of Drs. Jing Ning and Yu Shen. Research areas of interest include but are not limited to; development of statistical methods for integrating multiple data sources; machine learning approaches for complex biomedical data; and modeling of longitudinal data, survival analysis, and related methodologies.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
1. Gain expertise in biostatistics methodology research under the mentorship of Drs. Ning and Shen and develop independent and collaborative research abilities.
2. Innovate new statistical methods and machine learning approaches for the analysis of biomedical data and evaluate these methods through simulation studies and real data applications.
3. Write and submit research manuscripts to high-impact peer-reviewed journals to disseminate research findings and advance the field.
4. Attend and present research findings at scientific conferences and seminars to communicate results and engage in scientific discourse.
ELIGIBILITY REQUIREMENTS
We are seeking a highly motivated individual with a Ph.D. degree in statistics/biostatistics or a related field. The ideal candidate must have solid methodology training in statistics/biostatistics, as well as strong programming skills, particularly in R, Matlab, or Python, and preferably one lower-level computer language such as C. Expertise or skills in any of the following areas are desirable: survival data analysis for observational studies/electronic health records, data integration, conformal inference, transfer learning, and numerical optimization.
ADDITIONAL APPLICATION INFORMATION
Interested applicants should send a cover letter, statement of research interests, vitae and three references to yshen@mdanderson.org and jning@mdanderson.org (Subject line: Drs. Ning and Shen postdoc application).
POSITION INFORMATION
MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000 . depending on the number of years of postgraduate experience. 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
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
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

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