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From Home 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

... from developing sophisticated models for patient selection to creating AI-powered solutions for ... sciences (biotech, pharma, consulting) * Strong programming skills, particularly in Python

Valtech

Data Science Consultant

Plano, TX · Hybrid

$153K/yr

Valtech Solutions - Plano, TX needs a Data Science Consultant to refactor, optimize and automate ... Telecommuting and working from home permitted. Salary $153,160/yr. Send resumes to nam.recruitment ...

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From Home Biotech Data Science information

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$37.5K

$122.7K

$196.5K

How much do from home biotech data science jobs pay per year?

As of Jun 9, 2026, the average yearly pay for from home 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 is the difference between From Home Biotech Data Science vs From Home Biotech Bioinformatics Specialist?

AspectFrom Home Biotech Data ScienceFrom Home Biotech Bioinformatics Specialist
Required CredentialsBachelor's or Master's in Data Science, Bioinformatics, or related fieldsBachelor's or Master's in Bioinformatics, Computational Biology, or related fields
Work EnvironmentRemote, collaborative with data teamsRemote, often working with biological data and research teams
Industry UsageUsed across biotech, pharma, research institutionsPrimarily in biotech, research labs, and healthcare companies
Common Search/ComparisonYesYes

From Home Biotech Data Science focuses on analyzing biological data using statistical and machine learning techniques, while From Home Biotech Bioinformatics Specialist emphasizes managing and interpreting biological datasets, often involving sequence analysis and computational biology tools. Both roles are essential in biotech research but differ in their core skill sets and daily tasks.

More about From Home Biotech Data Science jobs
What cities are hiring for From Home Biotech Data Science jobs? Cities with the most From Home 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 From Home Biotech Data Science jobs? States with the most job openings for From Home Biotech Data Science jobs include:
What job categories do people searching From Home Biotech Data Science jobs look for? The top searched job categories for From Home Biotech Data Science jobs are:
From Home Biotech Data Science jobs near you
Infographic showing various From Home Biotech Data Science job openings in the United States as of May 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 87% Full Time, 10% Part Time, 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 6 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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