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Biostatistics Internships 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 ...

Alira Health

Career Day: Open Application

... future internships, entry-level roles, or project-based opportunities across various departments, including: * Clinical Trial Assistant (CTA) * Data Manager * Biostatistician and Statistical ...

Alira Health

Career Day: Open Application

... future internships, entry-level roles, or project-based opportunities across various departments, including: * Clinical Trial Assistant (CTA) * Data Manager * Biostatistician and Statistical ...

Alira Health

Career Day: Open Application

... future internships, entry-level roles, or project-based opportunities across various departments, including: * Clinical Trial Assistant (CTA) * Data Manager * Biostatistician and Statistical ...

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How much do biostatistics internships jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for biostatistics internships in the United States is $26.84, according to ZipRecruiter salary data. Most workers in this role earn between $23.32 and $29.81 per hour, depending on experience, location, and employer.

What are biostatistics internships?

Biostatistics internships are temporary positions, often for students or recent graduates, that provide hands-on experience in applying statistical methods to biological, medical, or public health research. Interns typically work alongside experienced biostatisticians to analyze data, interpret results, and assist with research projects. These internships help individuals gain practical skills, understand real-world applications of biostatistics, and build a foundation for careers in healthcare, pharmaceuticals, or academic research.

What types of projects do biostatistics interns typically work on, and how do these experiences support future career opportunities?

Biostatistics interns often contribute to a variety of projects, such as analyzing clinical trial data, supporting epidemiological studies, or developing statistical models for public health research. These hands-on experiences allow interns to apply statistical software tools like R or SAS, interpret real-world data, and collaborate with multidisciplinary teams including data scientists, clinicians, and researchers. Exposure to these projects not only builds practical skills but also provides valuable insights into industry standards and practices, helping interns stand out when pursuing full-time roles or advanced degrees.

What are the key skills and qualifications needed to thrive in biostatistics internships, and why are they important?

To thrive in Biostatistics Internships, you need a solid understanding of statistics, mathematics, and biology, often backed by progress toward a relevant degree. Familiarity with statistical software such as R, SAS, or Python and experience with data management tools are typically required. Strong analytical thinking, attention to detail, and effective communication skills help interns interpret and present complex data clearly. These skills are vital for producing accurate analyses that support research findings and inform public health or clinical decisions.

What is the difference between Biostatistics Internships vs Biostatistics Analyst?

AspectBiostatistics InternshipsBiostatistics Analyst
Required CredentialsUndergraduate or graduate student in biostatistics, public health, or related fieldBachelor's or master's degree in biostatistics, statistics, or related field
Work EnvironmentInternship programs in research institutions, healthcare companies, or universitiesFull-time roles in healthcare, pharmaceutical, or research organizations
Employer & Industry UsageEducational and training-focused, often temporaryProfessional, ongoing employment in health and research sectors

Biostatistics Internships are typically short-term training positions for students gaining experience, while Biostatistics Analysts are full-time professionals conducting data analysis and research. Internships focus on learning and skill development, whereas analysts apply their expertise to real-world projects in healthcare and research settings.

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Biostatistics Internships jobs near you
Infographic showing various Biostatistics Internships job openings in the United States as of August 2026, with employment types broken down into 9% Internship, 1% As Needed, 76% Full Time, 13% Part Time, and 1% Contract. Highlights an 91% Physical, 5% Hybrid, and 4% Remote job distribution, with an average salary of $55,819 per year, or $26.8 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

Posted 24 days ago

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