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Data Science Fall Internship Jobs in Raleigh, NC

She received postdoctoral training at Department of Data Science, Dana-Farber Cancer Institute and ... Hereceived Amazon Research Award (Fall 2024 and Spring 2025), Cisco Faculty Award (2024 and 2025 ...

She received postdoctoral training at Department of Data Science, Dana-Farber Cancer Institute and ... Hereceived Amazon Research Award (Fall 2024 and Spring 2025), Cisco Faculty Award (2024 and 2025 ...

AI/ML Intern

Durham, NC · On-site

$14.50 - $19.25/hr

Principal Responsibilities We are seeking AI/ML Interns to join our AI & Innovation team. Our team ... You will collaborate closely with our engineering and data science teams to bring AI-driven ...

New

AI/ML Intern

Durham, NC · On-site

$14.50 - $19.25/hr

Principal Responsibilities We are seeking AI/ML Interns to join our AI & Innovation team. Our team ... You will collaborate closely with our engineering and data science teams to bring AI-driven ...

New

AI/ML Intern

Durham, NC

$14.50 - $19.25/hr

Principal Responsibilities We are seeking AI/ML Interns to join our AI & Innovation team. Our team ... You will collaborate closely with our engineering and data science teams to bring AI-driven ...

New

We are seeking AI/ML Interns to join our AI & Innovation team. Our team is building the next ... You will collaborate closely with our engineering and data science teams to bring AI-driven ...

New

AI/ML Intern

Durham, NC · On-site

$14.50 - $19.25/hr

Principal Responsibilities We are seeking AI/ML Interns to join our AI & Innovation team. Our team ... You will collaborate closely with our engineering and data science teams to bring AI-driven ...

New

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Data Science Fall Internship information

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How much do data science fall internship jobs pay per hour?

As of May 29, 2026, the average hourly pay for data science fall internship in Raleigh, NC is $21.88, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $23.85 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Fall Intern, and why are they important?

To thrive as a Data Science Fall Intern, you generally need a solid foundation in statistics, programming (often Python or R), and data analysis, typically supported by coursework or experience in computer science, mathematics, or related fields. Familiarity with tools like pandas, scikit-learn, SQL, and data visualization libraries, as well as version control systems like Git, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help interns interpret data insights and collaborate with team members. These competencies are essential for producing actionable analyses and contributing meaningfully to data-driven projects in a short-term, fast-paced internship environment.

What types of projects can I expect to work on during a Data Science Fall Internship?

As a Data Science Fall Intern, you can expect to work on projects involving data cleaning, exploratory data analysis, and the development of predictive models using real-world datasets. Interns often collaborate with full-time data scientists and cross-functional teams to solve business problems, such as improving user engagement, optimizing processes, or generating actionable insights from large data sets. You may also participate in regular team meetings, present findings, and contribute to ongoing research or tool development. This hands-on experience helps you build both technical and communication skills within a dynamic and supportive environment.

What is a Data Science Fall Internship?

A Data Science Fall Internship is a temporary, structured work experience offered by organizations during the fall semester, designed for students or recent graduates interested in data science. Interns typically work on real-world projects involving data collection, analysis, machine learning, and visualization under the guidance of experienced data scientists. This internship provides hands-on experience, exposure to industry tools and techniques, and helps participants build valuable skills for future careers in data science. It also offers networking opportunities and a chance to explore potential career paths within the field.

What is the difference between Data Science Fall Internship vs Data Analyst Intern?

AspectData Science Fall InternshipData Analyst Intern
Required CredentialsEnrolled in or recent graduate of a related field (e.g., Data Science, Computer Science, Statistics)Enrolled in or recent graduate of a related field (e.g., Data Analysis, Business, Statistics)
Work EnvironmentTech companies, startups, research labs, often collaborative and project-basedBusiness firms, consulting agencies, often focused on reporting and data visualization
Employer & Industry UsageUsed by tech firms, finance, healthcare, and academia for entry-level talentCommon in corporate, marketing, and consulting sectors for supporting decision-making

The Data Science Fall Internship and Data Analyst Intern roles share similarities in required education and work environment but differ in focus. Data Science internships emphasize machine learning, programming, and statistical modeling, while Data Analyst internships focus more on data visualization, reporting, and business insights. Both are valuable entry points into data careers, often overlapping in skills but serving different industry needs.

What cities near Raleigh, NC are hiring for Data Science Fall Internship jobs? Cities near Raleigh, NC with the most Data Science Fall Internship job openings:
Infographic showing various Data Science Fall Internship job openings in Raleigh, NC as of May 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $45,502 per year, or $21.9 per hour.
Staff Software Engineer - Data Team (Menlo Park, CA) #4433

Staff Software Engineer - Data Team (Menlo Park, CA) #4433

GRAIL

Durham, NC

Full-time

Posted 22 days ago


Job description

Our mission is to detect cancer early, when it can be cured. We are working to change the trajectory of cancer mortality and bring stakeholders together to adopt innovative, safe, and effective technologies that can transform cancer care.

We are a healthcare company, pioneering new technologies to advance early cancer detection. We have built a multi-disciplinary organization of scientists, engineers, and physicians and we are using the power of next-generation sequencing (NGS), population-scale clinical studies, and state-of-the-art computer science and data science to overcome one of medicine’s greatest challenges.

GRAIL is headquartered in the bay area of California, with locations in Washington, D.C., North Carolina, and the United Kingdom. It is supported by leading global investors and pharmaceutical, technology, and healthcare companies.

For more information, please visit grail.com

GRAIL is seeking a Staff Software Engineer for the Data Team.  This team designs, builds, and operates the software systems that manage GRAIL’s end-to-end data lifecycle, from sample ingestion through downstream analysis, while meeting rigorous clinical, regulatory, and privacy standards. Our work directly supports clinical research, operations, and decision-making in the fight against cancer.
 
In this role, you will take technical ownership of systems that produce trusted, analysis-ready datasets for use across GRAIL’s research and clinical programs. This is a software engineering role focused on building complex production-grade systems that work with data in dynamic, regulated environments as opposed to assembling off-the-shelf ETL tools or writing SQL heavy pipelines,.This position offers significant autonomy and scope for impact. You’ll collaborate closely with research, clinical lab operations, and scientific teams, and lead efforts to improve how we structure, validate, and deliver critical scientific and clinical data.
 
This is a hybrid role based in either Menlo Park, CA (moving to Sunnyvale, CA in Fall 2026) or Durham, NC. Our current hybrid policy requires on-site presence at least 60% of the time, including key in-person collaboration days.
Responsibilities
  • Design and implement software systems that turn raw clinical, lab, and operational data into reliable, analysis-ready datasets
  • Partner with scientists, clinicians, lab operations, and data teams to understand data generation, transformation, and usage needs
  • Develop services, libraries, data models, and workflow components that enforce data integrity, access control, and compliance by design
  • Navigate complex data requirements such as schema evolution, blinding, consent, and privacy compliance
  • Collaborate on cross-functional initiatives involving data quality, testing strategy, monitoring, and operational excellence
  • Lead software engineering efforts for long-lived systems that must evolve alongside active clinical and research programs
  • Mentor engineers and collaborate with scientists to ensure software decisions support both technical and scientific outcomes
  • [Contribute to documentation, onboarding materials, and processes that support cross-functional adoption and data literacy across teams]
  • [Participate in incident response or investigation processes related to data quality or availability issues in production systems]
 
These responsibilities summarize the role’s primary responsibilities and are not an exhaustive list. They may change at the company’s discretion.
Required Qualifications
  • 7+ years of experience building production-grade software systems
  • Strong software engineering fundamentals, including system design, data modeling, API design, and writing well-tested production code.
  • Experience building and operating data-intensive software systems, not just declarative pipelines or SQL-only workflows
  • Proficiency in Go or Python (or similar general-purpose language)
  • Experience with data modeling, validation, and transforming real-world data into usable formats
  • BS in Computer Science, Engineering or Bioinformatics, or a related field, or equivalent practical experience
 
Preferred Qualifications
  • 2+ years experience working in regulated or clinical data environments (e.g., HIPAA, CLIA, GCP, FDA compliance)
  • Direct experience working with or supporting scientific teams (e.g., bioinformatics, wet lab, clinical research)
  • Experience designing systems that manage laboratory or bioinformatics data (e.g., LIMS, sequencing pipelines, assay metadata)
  • Familiarity with GxP practices and regulatory reporting requirements in clinical studies is a plus
  • Prior experience working in biotech, diagnostics, or life sciences companies
  • Experience supporting sample tracking, structured scientific data pipelines, or cross-functional data lifecycle management
  • Experience designing systems with data sequestration, permissioning, or privacy controls
  • Experience writing or contributing to software libraries, shared tooling, or reusable components used by other teams
  • Advanced degree (MS or PhD) in computer science, engineering, bioinformatics or a related discipline
Expected full time annual base pay scale for the bay area is $163K-$216K. Actual base pay will consider skills, experience and location.

This role may be eligible for other forms of compensation, including an annual bonus and/or incentives, subject to the terms of the applicable plans and Company discretion. This range reflects a good-faith estimate of the range that the Company reasonably expects to pay for the position upon hire; the actual compensation offered may vary depending on factors such as the candidate’s qualifications. Employees in this role are also eligible for GRAIL’s comprehensive and competitive benefits package, offered in accordance with our applicable plans and policies. This package currently includes flexible time-off or vacation; a 401(k) retirement plan with employer match; medical, dental, and vision coverage; and carefully selected mindfulness programs.

GRAIL is an equal employment opportunity employer, and we are committed to building a workplace where every individual can thrive, contribute, and grow. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, age, disability, status as a protected veteran, , or any other class or characteristic protected by applicable federal, state, and local laws. Additionally, GRAIL will consider for employment qualified applicants with arrest and conviction records in a manner consistent with applicable law and provide reasonable accommodations to qualified individuals with disabilities. Please contact us at rc@grailbio.com if you require an accommodation to apply for an open position.

GRAIL maintains a drug-free workplace. We welcome job-seekers from all backgrounds to join us!