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Internship Biotech Data Analyst Jobs (NOW HIRING)

Stellar IT Group

BioTech Data Engineer

Saint Louis, MO · On-site

$111K - $133K/yr

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 ...

ConnectPrep

Data Analyst Internship

Boston, MA · Remote

We are offering a Data Analyst Internship for qualified candidates. This is a cross-disciplinary role, both instructional and technical. You'll engage with our team of educators to validate and ...

ConnectPrep

Data Analyst Internship

Boston, MA · On-site +1

We are offering a Data Analyst Internship for qualified candidates. This is a cross-disciplinary role, both instructional and technical. You'll engage with our team of educators to validate and ...

ConnectPrep

Data Analyst Internship

Boston, MA · On-site +1

We are offering a Data Analyst Internship for qualified candidates. This is a cross-disciplinary role, both instructional and technical. You'll engage with our team of educators to validate and ...

PURIS Corporation, LLC

Data Analyst

Spring, TX · On-site

$85K - $95K/yr

Hands-on experience with Microsoft Power BI (coursework, internships, or projects). * DOMO experience is preferred but not required * Familiarity with data analysis tools such as Excel (pivot tables ...

Vector Resources, Inc

Data Analyst

Washington, DC · On-site

$100K - $150K/yr

... biotech, advanced semiconductors, material characterization). * Working proficiency in R for ... Familiarity with supply chain analytics, trade data (Panjiva, ImportGenius, UN Comtrade), corporate ...

Vector Resources, Inc

Data Analyst

Washington, DC · On-site

$100K - $150K/yr

... biotech, advanced semiconductors, material characterization). * Working proficiency in R for ... Familiarity with supply chain analytics, trade data (Panjiva, ImportGenius, UN Comtrade), corporate ...

CAREERS | vector

Data Analyst

Washington, DC · Hybrid

... biotech, advanced semiconductors, material characterization). * Working proficiency in R for ... Familiarity with supply chain analytics, trade data (Panjiva, ImportGenius, UN Comtrade), corporate ...

Radford University

Data Analyst

Radford, VA

$38K/yr

Proficiency in key data analysis and visualization tools such as SQL, Python, R, Excel, Tableau, Cognos, or Power BI demonstrated through academic projects, internships, or personal work. Strong ...

Radford University

Data Analyst

Radford, VA · On-site

$38K/yr

Proficiency in key data analysis and visualization tools such as SQL, Python, R, Excel, Tableau, Cognos, or Power BI demonstrated through academic projects, internships, or personal work. Strong ...

Rogue Fitness

Data Analyst

Columbus, OH · On-site

Overview The Data Analyst partners across Finance, Accounting, Supply Chain, and Operations to ... internships, or projects are encouraged to apply * Working knowledge of SQL (writing queries, joins ...

Rogue Fitness

Data Analyst

Columbus, OH · On-site

Overview The Data Analyst partners across Finance, Accounting, Supply Chain, and Operations to ... internships, or projects are encouraged to apply * Working knowledge of SQL (writing queries, joins ...

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Internship Biotech Data Analyst information

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How much do internship biotech data analyst jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for internship biotech data analyst in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is the difference between Internship Biotech Data Analyst vs Biotech Data Scientist?

AspectInternship Biotech Data AnalystBiotech Data Scientist
Required CredentialsEnrolled in or recent graduate of related degree (e.g., biology, bioinformatics, data analysis)Advanced degree (Master's or PhD) in data science, bioinformatics, or related fields
Work EnvironmentInternship setting in biotech or pharmaceutical companies, labs, or research institutionsFull-time role in biotech firms, research centers, or biotech startups
Employer & Industry UsageUsed for entry-level training, skill development, and gaining industry experienceUsed for advanced data analysis, modeling, and research projects

The Internship Biotech Data Analyst is an entry-level position focused on gaining practical experience in biotech data analysis, often requiring relevant coursework or a recent degree. In contrast, a Biotech Data Scientist typically holds advanced degrees and performs complex data modeling and research tasks. The internship provides foundational skills, while the data scientist role involves more specialized expertise and responsibilities.

What types of projects or data sets might I work with as an Internship Biotech Data Analyst?

As an Internship Biotech Data Analyst, you can expect to work with real-world biological or clinical data, such as genomic sequences, protein structures, or patient trial results. Projects often involve cleaning, analyzing, and visualizing these datasets to support research or product development. You'll likely collaborate closely with scientists, senior analysts, and sometimes software engineers to interpret findings and present actionable insights. This hands-on experience not only strengthens your technical skills but also helps you understand how data analysis drives innovation in the biotech industry.

What are the key skills and qualifications needed to thrive as an Internship Biotech Data Analyst, and why are they important?

To thrive as an Internship Biotech Data Analyst, you need a foundation in biology or biotechnology, statistical analysis, and data interpretation, typically gained through coursework or relevant internships. Familiarity with data analysis tools such as Python, R, Excel, and experience with bioinformatics databases or platforms like BLAST is highly beneficial. Strong attention to detail, problem-solving abilities, and effective communication skills make candidates stand out in this role. These competencies are crucial for accurately analyzing complex biological data, supporting research projects, and conveying findings to multidisciplinary teams.

What does an Internship Biotech Data Analyst do?

An Internship Biotech Data Analyst supports research and development teams in biotechnology companies by collecting, processing, and analyzing complex biological data. They use statistical tools and software to interpret experimental results, identify trends, and help drive decision-making in projects such as drug discovery, genomics, or clinical trials. Interns often work alongside experienced data analysts and scientists, gaining hands-on experience with real-world datasets and contributing to ongoing research efforts.
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Internship Biotech Data Analyst jobs near you
Infographic showing various Internship Biotech Data Analyst job openings in the United States as of May 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

BioTech Data Engineer

Stellar IT Group

Saint Louis, MO • On-site

$111K - $133K/yr

Full-time

Posted 6 days ago

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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