2

Biotech Data Science Remote Jobs (NOW HIRING)

BioTech Data Engineer

Saint Louis, MO · Remote

$111K - $133K/yr

Remote The Biotech Data Engineer focuses on designing, building, and maintaining scalable Azure ... science, and operational use cases * Lead data engineering initiatives that enable AI/ML model ...

Biotech Health Data Governance Lead (AI Training) About the Role What if your expertise in biotech ... scientific discovery, regulatory filings, and advanced AI-driven analytics. This is a fully remote ...

Contract on W2 (Need US Citizens or GC Holders or GC EAD or OPT or EAD or CPT) Hybrid to remote 3 days on site Education: Prefer a degree in data science, statistics, applied analytics, computer ...

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

... and biotechnology fields. Fullpower's B2B PaaS customers are in medical solutions, remote ... The ideal candidate will have a strong background in machine learning and data science and a proven ...

AI/ML Data Scientist (Remote) We are seeking an AI/ML Data Scientist for our client for a remote position. US Citizens or Green Card Holders ONLY!! No C2C No Third Party Agencies . What you'll do ...

next page

Showing results 1-20

Biotech Data Science Remote information

See salary details

$41.5K

$142.5K

$201K

How much do biotech data science remote jobs pay per year?

As of Jun 5, 2026, the average yearly pay for biotech data science remote in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Biotech Data Scientist in a remote role, you need a strong background in biology or biotechnology, advanced data analysis skills, and proficiency in programming languages like Python or R, often supported by a relevant degree. Familiarity with bioinformatics tools, machine learning frameworks, and cloud-based collaboration platforms is typically required. Excellent communication, problem-solving abilities, and self-motivation are crucial soft skills for effective remote teamwork and project delivery. These competencies ensure accurate data-driven insights, seamless remote collaboration, and impactful contributions to biotech research and innovation.

What are some common challenges faced by remote biotech data scientists, and how can they be addressed?

Remote biotech data scientists often encounter challenges related to cross-disciplinary collaboration and data accessibility, as projects frequently require input from wet lab scientists, clinicians, and IT specialists. Effective communication tools, regular virtual meetings, and clear project management protocols can help bridge these gaps. Additionally, ensuring secure and reliable access to large and sensitive datasets is essential, so familiarity with cloud platforms and data governance best practices is beneficial for success in this role.

What is a remote biotech data scientist?

A remote biotech data scientist is a professional who applies data analysis, machine learning, and statistical methods to biological and biomedical data while working from a location outside of a traditional office. They help interpret complex datasets from experiments, clinical trials, or genomics to aid in research, drug development, and healthcare innovation. Their work involves programming, data visualization, and collaborating with cross-functional teams, all done virtually. Remote biotech data scientists typically use tools like Python, R, and specialized bioinformatics software to analyze data and generate insights.
More about Biotech Data Science Remote jobs
What cities are hiring for Biotech Data Science Remote jobs? Cities with the most Biotech Data Science Remote 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 Biotech Data Science Remote jobs? States with the most job openings for Biotech Data Science Remote jobs include:
What job categories do people searching Biotech Data Science Remote jobs look for? The top searched job categories for Biotech Data Science Remote jobs are:
Infographic showing various Biotech Data Science Remote job openings in the United States as of May 2026, with employment types broken down into 3% Internship, 84% Full Time, 8% Part Time, and 5% Contract. Highlights an 100% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.

BioTech Data Engineer

Stellar IT Group

Saint Louis, MO • Remote

$111K - $133K/yr

Other

This job post has expired today. Applications are no longer accepted.


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