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Full Time Biotech Data Science Jobs (NOW HIRING)

Stellar IT Group

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 ...

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 ... The ideal candidate will have a strong background in machine learning and data science and a proven ...

Optimize Partners

Director, Data Science

New York, NY · Hybrid

One of our clients, a fast growing FinTech company that provides an online marketplace for commercial loans to small businesses, is looking to hire a full-time Director, Data Science to lead ...

Optimize Partners

Director, Data Science

New York, NY · On-site

One of our clients, a fast growing FinTech company that provides an online marketplace for commercial loans to small businesses, is looking to hire a full-time Director, Data Science to lead ...

Optimize Partners

Director, Data Science

New York, NY · Hybrid

One of our clients, a fast growing FinTech company that provides an online marketplace for commercial loans to small businesses, is looking to hire a full-time Director, Data Science to lead ...

Formation Bio

Director, Data Science

Boston, MA · On-site

$235K - $307K/yr

About the Position As the Director of Data Science at Formation Bio, you will be at the forefront ... sciences (biotech, pharma, consulting) * Strong programming skills, particularly in Python

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Full Time Biotech Data Science information

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$122.7K

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How much do full time biotech data science jobs pay per year?

As of Jun 5, 2026, the average yearly pay for full time biotech data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Full Time Biotech Data Scientist, you need a solid background in biology or biotechnology, advanced statistical analysis, and programming skills (such as Python or R), typically supported by a relevant degree (e.g., bioinformatics, computational biology, or data science). Familiarity with bioinformatics tools, machine learning frameworks, and database management systems is essential, along with experience using platforms like TensorFlow, scikit-learn, or SQL. Strong problem-solving abilities, communication skills, and the ability to work collaboratively with multidisciplinary teams are key soft skills for this role. These competencies enable effective extraction, analysis, and interpretation of complex biological data, driving innovative solutions and impactful research in biotech environments.

What are some common challenges faced by data scientists working in biotech, and how can these be addressed?

Data scientists in biotech often encounter challenges such as handling complex and high-dimensional biological data, integrating heterogeneous data types (like genomic, clinical, and imaging data), and ensuring data quality and reproducibility. Collaborating closely with biologists, clinicians, and other domain experts is crucial for understanding the context and nuances of the data. Continuous learning, leveraging robust data-cleaning pipelines, and using specialized bioinformatics tools can help overcome these obstacles and contribute to impactful discoveries in the biotech field.

What is a Full Time Biotech Data Science job?

A Full Time Biotech Data Science job involves using data analysis, statistical modeling, and machine learning techniques to solve problems in the biotechnology field. Professionals in this role work with large biological data sets, such as genomic, proteomic, or clinical data, to derive insights that support research, drug development, or healthcare innovations. They often collaborate with biologists, chemists, and software engineers to develop data-driven solutions for complex biological challenges. This role typically requires a strong background in both life sciences and data science, as well as proficiency with programming languages like Python or R.

What is the difference between Full Time Biotech Data Science vs Full Time Bioinformatics Data Scientist?

AspectFull Time Biotech Data ScienceFull Time Bioinformatics Data Scientist
Required CredentialsBachelor's or Master's in Data Science, Bioinformatics, or related fields; programming skills in Python, RBachelor's or Master's in Bioinformatics, Computational Biology, or related fields; programming skills in Python, R
Work EnvironmentPharmaceutical companies, biotech firms, research labsResearch institutions, biotech companies, healthcare organizations
Industry UsageData analysis, predictive modeling, clinical trial dataGenomic data analysis, sequence alignment, biological data interpretation

Full Time Biotech Data Science focuses on analyzing biological data using data science techniques, often involving clinical and experimental data. Full Time Bioinformatics Data Scientist specializes in interpreting genomic and biological datasets, emphasizing sequence analysis and biological insights. Both roles require similar skills but differ in their primary data types and application areas.

More about Full Time Biotech Data Science jobs
What cities are hiring for Full Time Biotech Data Science jobs? Cities with the most Full Time 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 Full Time Biotech Data Science jobs? States with the most job openings for Full Time Biotech Data Science jobs include:
What job categories do people searching Full Time Biotech Data Science jobs look for? The top searched job categories for Full Time Biotech Data Science jobs are:
Full Time Biotech Data Science jobs near you
Infographic showing various Full Time Biotech Data Science job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 97% Full Time, 1% Contract, and 1% Nights. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

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

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