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Biotech Data Scientist Internship Jobs (NOW HIRING)

Stellar IT Group

BioTech Data Engineer

Saint Louis, MO · Remote

$111.30K - $133.70K/yr

Biotech Data Engineer Job Type: FTE Work Mode: Remote The Biotech Data Engineer focuses on ... science, and operational use cases * Lead data engineering initiatives that enable AI/ML model ...

Stellar IT Group

BioTech Data Engineer

Saint Louis, MO · On-site

$111.30K - $133.70K/yr

Biotech Data Engineer Job Type: FTE Work Mode: Remote The Biotech Data Engineer focuses on ... science, and operational use cases * Lead data engineering initiatives that enable AI/ML model ...

Conversica, Inc

Data Scientist

Seattle, WA · On-site

... for data science interns in the areas of natural language processing, natural language generation, and deep learning. Recognized by Gartner, INC, Harvard Business Review, etc, we are passionate ...

Strayos

$13 - $17.50/hr

... internship opportunity. Here at Strayos, we use advanced computer vision and machine learning on ... data to build insights for Mining, Infrastructure and Construction industry. Our applied science ...

Alignerr

Biotech Health Data Governance Lead What if your expertise in biotech data governance could ... Your work will sit at the intersection of cutting-edge AI development and regulated life sciences ...

State Farm

Data Scientist

Richardson, TX · Hybrid

Lead/mentor other Data Scientists, interns, and other technical work teams * Make strategic recommendations on data collection, integration, and retention requirements, incorporating business ...

State Farm

Data Scientist

Bloomington, IL · Hybrid

Lead/mentor other Data Scientists, interns, and other technical work teams * Make strategic recommendations on data collection, integration, and retention requirements, incorporating business ...

State Farm

Data Scientist

Dunwoody, GA · Hybrid

Lead/mentor other Data Scientists, interns, and other technical work teams * Make strategic recommendations on data collection, integration, and retention requirements, incorporating business ...

State Farm

Data Scientist

Tempe, AZ · Hybrid

Lead/mentor other Data Scientists, interns, and other technical work teams * Make strategic recommendations on data collection, integration, and retention requirements, incorporating business ...

Fullpower Technologies

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

... and biotechnology. Fullpower's platform is vetted and deployed as a PaaS, backed by a patent ... Fullpower is seeking a passionate, team-oriented, and self-motivated Data Scientist interested in ...

Fullpower Technologies, Inc.

Data Scientist

Santa Cruz, CA · On-site

$130K - $170K/yr

... and biotechnology. Fullpower's platform is vetted and deployed as a PaaS, backed by a patent ... Fullpower is seeking a passionate, team-oriented, and self-motivated Data Scientist interested in ...

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Biotech Data Scientist Internship information

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$46K

$165K

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How much do biotech data scientist internship jobs pay per year?

As of May 28, 2026, the average yearly pay for biotech data scientist internship in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Biotech Data Scientist Intern, you need a solid understanding of statistics, biology, and data analysis, often supported by coursework or a degree in bioinformatics, computer science, or a related field. Familiarity with programming languages like Python or R, experience with data visualization tools, and knowledge of bioinformatics databases and pipelines are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help set top candidates apart. These skills and qualities ensure meaningful data insights, accurate research results, and clear collaboration across multidisciplinary teams in the biotech field.

What types of projects and data sets do Biotech Data Scientist Interns typically work with during their internship?

Biotech Data Scientist Interns often work with a variety of biological and clinical data sets, including genomic, proteomic, and experimental data. Projects may involve analyzing large-scale sequencing data, building predictive models for drug discovery, or developing algorithms to interpret laboratory results. Interns usually collaborate closely with bioinformaticians, wet-lab scientists, and software engineers, gaining hands-on experience with data cleaning, visualization, and statistical analysis. This exposure not only sharpens technical skills but also provides valuable insight into real-world biotech research workflows.

What is a Biotech Data Scientist Internship?

A Biotech Data Scientist Internship is a temporary position where students or recent graduates work at the intersection of biotechnology and data science. Interns typically analyze large biological datasets, apply machine learning techniques, and help interpret experimental results to support research and development in biotech companies. This internship provides hands-on experience with bioinformatics tools, data visualization, and statistical analysis. It is designed to help interns develop practical skills, gain industry exposure, and contribute to real-world biotech projects.
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Biotech Data Scientist Internship jobs near you
Infographic showing various Biotech Data Scientist Internship job openings in the United States as of May 2026, with employment types broken down into 5% Internship, 5% As Needed, 11% Full Time, and 79% Part Time. Highlights an 13% Physical, and 87% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

BioTech Data Engineer

Stellar IT Group

Saint Louis, MO • Remote

$111.30K - $133.70K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Overview:
Job Title: Biotech Data Engineer
Job Type: FTE
Work Mode: Remote
The Biotech Data Engineer focuses on designing, building, and maintaining scalable Azure Databricks-based data pipelines and architectures that enable analytics, AI/ML, and reporting across commercial functions. It involves leading data engineering initiatives, ensuring governance and compliance, optimizing performance and costs, and collaborating across teams to advance the company's data and AI strategy. The role reports to the Director of Business Intelligence.
Roles & Responsibilities
  • Design, build, and maintain scalable, reliable, and cost-efficient data pipelines using Azure Databricks in support of analytics, machine learning, data science, and operational use cases
  • Lead data engineering initiatives that enable AI/ML model development, LLM integrations, and AI-driven applications while ensuring scalability and alignment with enterprise and business priorities
  • Architect and implement data integration frameworks across diverse Adtech and Martech ecosystems, incorporating Google Analytics, media campaign data, and third-party marketing APIs like Salesforce
  • Manage and optimize data ingestion, transformation, and storage processes using SQL, Python, and PySpark to integrate structured and unstructured data sources
  • Design and maintain API integrations with internal and external systems, including Python- and PySpark-based services and AI/LLM-powered APIs for advanced analytics and automation
  • Administer and maintain Azure-based data tools and platforms (e.g., Databricks, ADF) to ensure operational excellence, reliability, and security
  • Collaborate with internal stakeholders and external partners to evolve data platform design and architecture that supports advanced analytics, personalization, marketing intelligence, and marketing automation
  • Execute against the company's data and AI strategy by translating strategic goals into technical architecture, design and requirement documents, and implementation roadmaps
  • Ensure data quality, integrity, and consistency through robust validation, monitoring, and alerting mechanisms within Azure Databricks
  • Implement and enforce data governance, security, and compliance standards in collaboration with IT, InfoSec, and data governance teams
  • Partner with analytics, marketing, commercial operations, and core technology/cybersecurity teams to deliver fit-for-purpose commercial data products
  • Monitor and optimize data infrastructure costs, performance, and scalability across Azure cloud environments
  • Develop and maintain architecture documentation, pipeline specifications, and design diagrams for transparency and knowledge sharing with technical and business stakeholders
  • Participate in architecture discussions, design reviews, and CI/CD workflows to ensure high-quality engineering and deployment practices as part of an Agile engineering team
  • Continuously evaluate and recommend new Azure services, designs, improvements, frameworks, and AI integration tools to enhance our data platform
  • Drive automation, observability, and standardization across data workflows to improve efficiency and reduce manual intervention
  • Complete all job duties in compliance with company policy, SOPs, safety rules, and applicable federal, state, and local regulations
Education & Licenses And Experience
Bachelor of science degree required. A minimum of 5 years transferable working experience in the area of operational support of a Data Engineering, Data Architecture, or Cloud Platforms function preferred. The ideal candidate will have recent and relevant experience in the pharma or biotech industry.
Required Competencies & Skills
  • Experience with Azure Cloud (Databricks, DevOps, DataFactory)
  • Pharma / biotech domain experience, specifically within the commercial data space (sales, market access / payer, marketing)
  • Strong hands-on python, pyspark, and SQL skills
  • Direct experience with building and leveraging API integrations in ETL pipeline development
  • Experience integrating with current best-in-class AI models and APIs like OpenAI API, Databricks AI models, etc.
  • Self-driven with ability to independently design end-to-end data pipelines while ensuring architectural best practices
  • Ability to collaborate with a broad set of stakeholders to evaluate the business need and construct a technical design that can enable stakeholder priorities
  • Travel up to 20%
Preferred Competencies & Skills
  • Strong knowledge of and experience with maximizing business value using Databricks Unity Catalog or Databricks One capabilities
  • Familiarity with tools and practices in the Martech and Adtech landscape
  • Knowledge of Consumer, Patient, or HCP data ecosystems
  • Experience with identity providers like LiveRamp, Acxiom, Experian, etc.
  • Experience with custom-built or third-party Customer Data Platforms (CDP)
  • Experience with marketing automation tools

Skills:
Data Engineering

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