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Internship Biostatistics Jobs (NOW HIRING)

Foundation Medicine

Biostatistician I

Boston, MA · Hybrid

$103K - $124K/yr

Doctor of Philosophy in Statistics, Biostatistics, Computational Biology or other quantitative fields. * Work or internship experience as a biostatistician in biopharmaceutical or diagnostics ...

Jj

Principal Scientist, Biostatistics

Spring House, PA · On-site +1

Supervise contractors, special assignment personnel, interns, and/or co-ops as required. Mentor ... Biostatistics-related occupation. This job posting is anticipated to close on 8/30/2026 . Johnson ...

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How much do internship biostatistics jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for internship biostatistics in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What is an internship biostatistics?

Internship Biostatistics positions are temporary roles designed for students or recent graduates interested in applying statistical methods to biological, medical, or public health research. Interns in biostatistics support research projects by analyzing data, running statistical models, and helping interpret results under the guidance of experienced biostatisticians. These internships provide hands-on experience with real-world datasets, statistical software, and collaborative research environments. They are valuable for gaining practical skills and exploring potential careers in biostatistics, epidemiology, or related fields.

What types of projects do biostatistics interns typically work on, and how do these contribute to their learning and career development?

Biostatistics interns often participate in projects involving data analysis for clinical trials, epidemiological studies, or public health research. These projects usually require working with real-world datasets, performing statistical tests, and creating reports or visualizations to communicate findings. Interns frequently collaborate with statisticians, data managers, and scientists, gaining exposure to industry-standard software and methodologies. This hands-on experience not only builds practical skills but also offers valuable insights into career paths within pharmaceutical, healthcare, or academic settings.

What are the key skills and qualifications needed to thrive as an internship biostatistics, and why are they important?

To thrive as an Internship Biostatistics, you generally need a foundational knowledge of statistical methods, data analysis, and proficiency in mathematics, typically supported by coursework in biostatistics, statistics, or a related field. Familiarity with statistical software such as R, SAS, or SPSS and experience with data management systems are commonly expected. Strong analytical thinking, attention to detail, and effective communication skills enable you to interpret complex data and explain findings clearly. These competencies are crucial for producing reliable statistical analyses that inform research and guide evidence-based decision-making in healthcare and life sciences.

What is the difference between Internship Biostatistics vs Biostatistician?

AspectInternship BiostatisticsBiostatistician
Required CredentialsUndergraduate or graduate student, some coursework in biostatisticsMaster's or PhD in Biostatistics or related field
Work EnvironmentInternship setting, often in research or healthcare organizationsFull-time professional role in research, healthcare, or pharma
Employer & Industry UsageEducational institutions, research projects, internshipsHospitals, biotech companies, government agencies
Common Search & Comparison IntentLearning about entry-level opportunities in biostatisticsUnderstanding professional roles and career progression

Internship Biostatistics is an entry-level, educational position designed for students gaining practical experience, while a Biostatistician is a full-time professional responsible for analyzing data and supporting research in healthcare and related fields. Internships often serve as a stepping stone toward becoming a biostatistician.

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Internship Biostatistics jobs near you
Infographic showing various Internship Biostatistics job openings in the United States as of August 2026, with employment types broken down into 12% Internship, 58% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.

Biostatistics Scientist (Plant Science)

Sakata Seed America, INC.

Woodland, CA • On-site

$90K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago

Key responsibilities

  • Support the development, testing, and interpretation of statistical and genomic prediction models for vegetable crop breeding programs.

  • Analyze molecular marker datasets, including SNP and haplotype data, to support trait mapping, marker validation, and breeding decisions.

  • Prepare, manage, and analyze genomic, phenotypic, greenhouse, and field-trial datasets under guidance from senior team members.

Job description


JOB SUMMARY

The Biostatistics Scientist supports applied statistical analysis, quantitative genetics, and breeding analytics for vegetable crop research programs. This entry-level role contributes to genomic, phenotypic, and field-trial data analysis under the guidance of senior scientists, managers and cross-functional project teams. The position helps develop reliable, reproducible analytical workflows that improve trait evaluation, marker-assisted selection, genomic prediction, and data-driven breeding decisions.

Key Responsibilities

Statistical Analysis, Quantitative Genetics & Genomic Prediction

  • Support the development, testing, and interpretation of statistical and genomic prediction models for vegetable crop breeding programs.
  • Apply standard statistical and quantitative genetics methods, such as mixed models, heritability estimation, genetic correlations, and basic genomic prediction approaches.
  • Assist with evaluating model performance, prediction accuracy, and data quality across populations, environments, and breeding stages.
  • Contribute to analyses that help breeders understand trait variation, experimental results, and selection opportunities.
  • Document methods, assumptions, code, and results clearly to support reproducibility and team review.

Molecular Marker & Trait Analytics

  • Analyze molecular marker datasets, including SNP and haplotype data, to support trait mapping, marker validation, and breeding decisions.
  • Assist molecular and breeding teams with data summaries for marker development, marker deployment, and trait evaluation projects.
  • Support quality control of genotypic and phenotypic datasets, including data cleaning, formatting, consistency checks, and basic exploratory analysis.
  • Help prepare selection metrics, trait summaries, and visualizations that integrate multiple sources of breeding data.
  • Translate analytical results into concise summaries that can be reviewed by breeders, molecular scientists, and project teams.

Genomic, Phenotypic & Field Trial Data Analysis

  • Prepare, manage, and analyze genomic, phenotypic, greenhouse, and field-trial datasets under guidance from senior team members.
  • Develop and maintain reproducible scripts for data quality control, statistical analysis, visualization, and reporting.
  • Contribute to the improvement of analytical templates, reporting workflows, and shared data practices in collaboration with bioinformatics and data teams.

Project Support & Cross-Functional Collaboration

  • Support analytical components of breeding, trait development, molecular marker, and technology projects.
  • Collaborate with breeders, phenotyping, molecular biology, bioinformatics, and data teams to understand project objectives and data requirements.
  • Prepare clear technical summaries, tables, figures, and presentations to communicate results to internal stakeholders.
  • Learn and apply current methods in biostatistics, quantitative genetics, breeding analytics, and reproducible scientific computing.


Required Qualifications

Education

  • PhD in Biostatistics, Statistics, Quantitative Genetics, Plant Breeding, Computational Biology, Data Science, or a related field; industry experience a plus
    or
  • MS in Biostatistics, Statistics, Quantitative Genetics, Plant Breeding, Computational Biology, Data Science, or a related field with 0–2 years of relevant academic, internship; industry experience a plus


Experience & Technical Skills

  • Foundational training in statistics, biostatistics, quantitative genetics, plant breeding, computational biology, or related analytical disciplines.
  • Experience with statistical analysis of biological, genomic, phenotypic, field-trial, or experimental datasets through graduate research, internships, or applied projects.
  • Working knowledge of statistical programming in R, Python, SAS, or similar tools.
  • Good understanding of experimental design, mixed models, regression, data visualization, and reproducible analytical workflows.
  • Experience with molecular markers, genomic data, plant breeding concepts, or trait analysis is desirable.
  • Ability to learn new methods, manage multiple analytical tasks, and deliver accurate results with guidance.
  • Strong attention to detail, scientific curiosity, communication skills, and willingness to collaborate across disciplines.

Preferred Qualifications

  • Research experience in plant breeding, seed industry research, agricultural biotechnology, or applied life-science data analysis.
  • Experience in genomic prediction, QTL mapping, GWAS, marker-assisted selection, or trait discovery workflows.
  • Familiarity with breeding databases, phenotyping systems, laboratory information systems, or integrated data platforms.
  • Experience preparing figures, tables, dashboards, or technical reports for scientific or cross-functional audiences.
  • Exposure to cloud-based, Linux, Git, or high-performance computing environments for data analysis.
  • Interest in applying AI, machine learning, and modern statistical methods to practical breeding and research questions.

Competencies & Behaviors

  • Demonstrates curiosity, initiative, and accountability in learning new analytical methods and scientific workflows.
  • Applies statistical methods carefully, with attention to data quality, assumptions, and reproducibility.
  • Works collaboratively with scientists from breeding, molecular biology, phenotyping, bioinformatics, and data teams.
  • Communicates analytical results clearly to both technical and non-technical audiences.
  • Manages assigned tasks effectively, asks timely questions, and follows through on deliverables.
  • Contributes to a culture of scientific rigor, continuous improvement, teamwork, and practical problem solving.

Reporting Structure

  • Reports to Senior Biotech Manager

Works under the guidance of senior scientists, project leads, and cross-functional research teams

BENEFITS:

Health & Wellness
Medical, Dental & Vision Insurance
Monthly Wellness Stipend
Employee Assistance Program (EAP)

Employee Philanthropic Giving Program 

Disability Insurance (plans vary by location)


Financial Benefits
401(k) Program + Company Match
Profit Sharing Program (via 401(k)

Holiday Bonus

Performance Incentive Bonus Program
Tuition Reimbursement

529 College‑Savings Plan
Company-Paid Basic Life & AD&D Insurance


Time Off & Flexibility
Paid Vacation
Paid Sick Leave
15 Paid Company Holidays
2 Floating Holidays 

Birthday Off