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Intern Biotech Data Science Jobs (NOW HIRING)

BioTech Data Engineer

Saint Louis, MO · On-site

$111K - $133K/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 ...

Role Overview The Data Science Intern will help us to understand the performance of Executive Partners (XPs) and build advanced matching models to evaluate Athena's Executive Partners (XPs) and ...

Role Overview The Data Science Intern will help us to understand the performance of Executive Partners (XPs) and build advanced matching models to evaluate Athena's Executive Partners (XPs) and ...

As a Data Science Intern in our New York-based Data Lab, you will work at the forefront of the digital transformation of education data, supporting the development of innovative, data-driven ...

As a Data Scientist Intern, you'll dig into the data to uncover insights, identify opportunities for product improvements and new product development, define product metrics with goals, design ...

As a Data Scientist Intern, you'll dig into the data to uncover insights, identify opportunities for product improvements and new product development, define product metrics with goals, design ...

What you'll do as a Data Science Intern at Rundoo * Analyze data on product, sales and GTM hypotheses. * Translate product, sales and GTM requests into data problems & execute on them. * Build ...

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Position: Data Science and Analytics Intern Duration: 9 Weeks (15th June'26 - 14th Aug'26) Salary: $15.92 hourly (Minimum 20 hours per week) Location & Job Type: United States, Remote/Hybrid ...

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Intern Biotech Data Science information

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How much do intern biotech data science jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for intern biotech data science in the United States is $17.04, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is the difference between Intern Biotech Data Science vs Intern Bioinformatics?

AspectIntern Biotech Data ScienceIntern Bioinformatics
Required CredentialsUndergraduate or graduate degree in Data Science, Bioinformatics, or related fieldsUndergraduate or graduate degree in Bioinformatics, Biology, or related fields
Work EnvironmentLaboratories, biotech companies, research institutions focusing on data analysisLaboratories, research centers, biotech firms focusing on biological data analysis
Industry UsageUsed in biotech, pharmaceutical, and healthcare sectors for data-driven researchCommon in genomics, molecular biology, and personalized medicine sectors

Intern Biotech Data Science and Intern Bioinformatics both involve working with biological data, but Data Science roles focus more on statistical analysis, machine learning, and data modeling, while Bioinformatics roles emphasize biological data interpretation, sequence analysis, and computational biology. The choice depends on your background and career interests in either data-driven insights or biological data analysis.

What cities are hiring for Intern Biotech Data Science jobs? Cities with the most Intern Biotech Data Science job openings:
What are the most commonly searched types of Biotech Data Science jobs? The most popular types of Biotech Data Science jobs are:
What states have the most Intern Biotech Data Science jobs? States with the most job openings for Intern Biotech Data Science jobs include:

BioTech Data Engineer

Stellar IT Group

Saint Louis, MO • On-site

$111K - $133K/yr

Full-time

Posted 2 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