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Data Science Internship Biotech Jobs in Florida (NOW HIRING)

Data Science Associate (Governance) Company Overview At Mitsubishi Power, we're not just building better clean energy technologies; we're architecting a better future. Our team is boldly redefining ...

Job Summary: The Performance Coach Sports Science Internship is a hybrid, immersive program ... Passionate about athlete development and data-driven performance. Internship Logistics: If selected ...

Sports Science Intern - Fall 2026

Gulf Breeze, FL · On-site

$13.75 - $18.25/hr

Job Summary: The Performance Coach Sports Science Internship is a hybrid, immersive program ... Passionate about athlete development and data-driven performance. Internship Logistics: If selected ...

Data Scientist

Orlando, FL · On-site

$107K/yr

In this role, you will bridge the gap between theoretical data science and real-world operational ... Technical Leadership & Mentorship (10%) • Lead and manage a pipeline of talent, including interns ...

... Science, Applied Mathematics, Biotechnology preferred - Prior consulting or advisory firm ... data integration Travel Requirements Up to 80% Job Posting End Date The salary range for this ...

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Data Science Internship Biotech information

What are the key skills and qualifications needed to thrive as a data science intern in biotech, and why are they important?

A Data Science Intern in Biotech should have a solid understanding of statistics, data analysis, and programming (especially Python or R), typically supported by coursework in computer science, biology, or related fields. Familiarity with data visualization tools, bioinformatics databases, and platforms like Jupyter Notebook or Tableau is highly beneficial. Strong problem-solving abilities, curiosity, and effective communication help interns translate complex data into actionable insights for interdisciplinary teams. These skills enable interns to contribute meaningfully to biotech research by extracting and communicating value from large, complex biological datasets.

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

AspectData Science Internship BiotechData Analyst
Required CredentialsTypically pursuing or completed a degree in Data Science, Biotechnology, or related fieldsUsually holds a degree in Statistics, Mathematics, or related fields
Work EnvironmentBiotech companies, research labs, pharmaceutical firmsVarious industries including finance, healthcare, marketing
Industry UsageApplied to biotech research, drug development, genomicsApplied to business insights, reporting, and decision-making

While both roles involve data analysis skills, a Data Science Internship in Biotech focuses on applying data science techniques to biotech-specific problems, often requiring knowledge of biology or biotech tools. A Data Analyst generally works across industries, emphasizing data reporting and visualization. The internship provides hands-on experience in biotech settings, whereas a Data Analyst role is broader and industry-agnostic.

What is a data science internship in biotech?

A Data Science Internship in Biotech is a temporary, supervised position where interns apply data science techniques to biological and medical data within a biotechnology company. Interns typically work on real-world projects involving data analysis, machine learning, or bioinformatics to help solve challenges in drug discovery, genomics, or healthcare. The internship provides practical experience, helps interns develop valuable technical and domain-specific skills, and can lead to future job opportunities in the biotech industry.

What types of projects does a data science intern typically work on in biotech?

Data Science Interns in biotech companies often contribute to projects involving the analysis of large-scale biological data, such as genomic sequences or clinical trial results. They might work on building predictive models to assist with drug discovery, automating data processing workflows, or visualizing complex datasets for research teams. Interns regularly collaborate with biologists, chemists, and other data scientists, gaining exposure to interdisciplinary teamwork and the unique challenges of working with sensitive, high-dimensional biomedical data.
What cities in Florida are hiring for Data Science Internship Biotech jobs? Cities in Florida with the most Data Science Internship Biotech job openings:
Infographic showing various Data Science Internship Biotech job openings in Florida as of July 2026, with employment types broken down into 10% Internship, 40% Full Time, 40% Part Time, and 10% Temporary. Highlights an 100% In-person job distribution.

Data Science Internship (Data Platforms)

Mitsubishi Heavy Industries Group

Lake Mary, FL • On-site

Other

Posted 25 days ago


Job description

Data Science Associate

 

Company Overview

At Mitsubishi Power, we're not just building better clean energy technologies; we're architecting a better future. Our team is boldly redefining power generation to accelerate the world's energy transition. We operate as one team, pushing toward our vision of the future. We value problem solvers, prioritize collaboration, and support each other in an inclusive culture built on accountability and authenticity by demonstrating our values: Safety, Family, Innovative, Inclusive, Accountable & Courageous. Together, we're building the future we all aspire to - making net zero a reality.

Role Overview

The Data Scientist Intern supports Mitsubishi Power's IT Data Platforms team by contributing to data quality, data cataloging, and automation efforts within enterprise data environments. This hands-on internship provides practical experience working with cloud-based data platforms, centralized data repositories, and Microsoft Power Platform tools. The role collaborates with Data Platforms leadership, Enterprise Applications, and IT stakeholders to support scalable, high-quality data solutions used across the business. 

Key Responsibilities

  • Assist with data quality assessments across enterprise data sources, identifying gaps, inconsistencies, and improvement opportunities.
  • Support data catalog activities including documentation of datasets, metadata, data definitions, and lineage.
  • Validate, organize, and prepare ingested data within centralized platforms such as data lakes and structured repositories.
  • Contribute to automation efforts to surface data into Microsoft Power Apps and Power Automate workflows.
  • Perform data validation and reconciliation to ensure accuracy and completeness between source and ingested data.
  • Assist with development of basic dashboards, reports, and visualizations to support data visibility and usage.
  • Support testing and user acceptance activities to validate data processes and automation solutions.
  • Maintain tracking artifacts such as data quality logs, catalog trackers, and automation inventories.
  • Document data processes, standards, and learnings to support long-term platform sustainability.

 

 

Requirements

  • Assist with data quality assessments across enterprise data sources, identifying gaps, inconsistencies, and improvement opportunities.
  • Support data catalog activities including documentation of datasets, metadata, data definitions, and lineage.
  • Validate, organize, and prepare ingested data within centralized platforms such as data lakes and structured repositories.
  • Contribute to automation efforts to surface data into Microsoft Power Apps and Power Automate workflows.
  • Perform data validation and reconciliation to ensure accuracy and completeness between source and ingested data.
  • Assist with development of basic dashboards, reports, and visualizations to support data visibility and usage.
  • Support testing and user acceptance activities to validate data processes and automation solutions.
  • Maintain tracking artifacts such as data quality logs, catalog trackers, and automation inventories.
  • Document data processes, standards, and learnings to support long-term platform sustainability.


Learning Outcomes

  • Gain hands-on experience with enterprise data platforms, including data lakes and cloud-based environments, understanding how data supports business operations.
  • Develop core data skills in data quality, validation, cataloging, and metadata management using real-world datasets.
  • Apply analytics and automation tools such as Excel, SQL, and Microsoft Power Platform to support business processes and workflows.
  • Strengthen problem-solving and communication skills by working cross-functionally and translating data insights into clear, actionable outcomes.

 

Mitsubishi Power is an Equal Employment Opportunity (EEO) employer actively seeking to diversify the workforce and is committed to a policy of equal employment opportunity. Therefore, all qualified applicants regardless of race, color, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally recognized protected basis under applicable law, are strongly encouraged to apply.