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Flex 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 ...

Formation Bio

Director, Data Science

Boston, NY · 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

StubHub

Data Science Manager

New York, NY · Hybrid

The Data Science team, a part of the broader StubHub Data organization, is looking for an ... Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your ...

StubHub

Data Science Manager

Los Angeles, CA · Hybrid

The Data Science team, a part of the broader StubHub Data organization, is looking for an ... Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your ...

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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Flex Biotech Data Science information

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

To thrive as a Flex Biotech Data Scientist, you need a strong background in biology, statistics, and data analysis, typically supported by a degree in bioinformatics, computational biology, or a related field. Expertise in programming languages (such as Python or R), experience with bioinformatics tools, and familiarity with platforms like SQL databases and machine learning frameworks are essential. Strong problem-solving skills, collaboration, and the ability to communicate complex findings to non-technical stakeholders make candidates stand out. These skills are crucial for extracting actionable insights from complex biological data, driving innovation, and supporting research and development in biotech environments.

How do Flex Biotech Data Science professionals typically collaborate with laboratory and research teams?

Flex Biotech Data Science professionals often work closely with laboratory scientists and research teams to interpret experimental data, refine data collection methods, and translate complex results into actionable insights. This collaboration involves regular meetings to discuss ongoing projects, sharing data findings, and providing statistical expertise to optimize research outcomes. Effective communication and a solid understanding of both computational and biological concepts are essential for bridging the gap between data science and laboratory work.

What is a Flex Biotech Data Scientist?

A Flex Biotech Data Scientist is a professional who applies data science and analytical techniques within the biotechnology sector, often in flexible or cross-functional roles. They analyze large sets of biological and clinical data to support research, development, and innovation in biotech companies. Flex roles may involve working on various projects, collaborating with interdisciplinary teams, and utilizing skills in programming, statistics, and biology. Their work helps drive discoveries, optimize experiments, and improve decision-making processes in the biotech industry.

What is the difference between Flex Biotech Data Science vs Flex Biotech Data Analysis?

AspectFlex Biotech Data ScienceFlex Biotech Data Analysis
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fields; knowledge of programming languages like Python or RBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams in biotech or healthcare companies, often involving complex data modelingOperational settings focusing on data reporting, visualization, and supporting decision-making
Employer & Industry UsageUsed in biotech firms, pharmaceutical companies, and research institutionsCommon in biotech companies, healthcare providers, and research organizations

Flex Biotech Data Science roles focus on developing predictive models and advanced analytics, requiring programming skills and a strong statistical background. Flex Biotech Data Analysis positions emphasize interpreting data, creating reports, and supporting business decisions with less emphasis on coding. Both roles are vital in biotech but differ in technical complexity and responsibilities.

More about Flex Biotech Data Science jobs
What cities are hiring for Flex Biotech Data Science jobs? Cities with the most Flex 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 Flex Biotech Data Science jobs? States with the most job openings for Flex Biotech Data Science jobs include:
What job categories do people searching Flex Biotech Data Science jobs look for? The top searched job categories for Flex Biotech Data Science jobs are:
Flex Biotech Data Science jobs near you
Infographic showing various Flex Biotech Data Science job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, 3% Part Time, and 9% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution.

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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