ZipRecruiter

Log In

1

Trainee 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

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

next page

Showing results 1-20

People also search for

All JobsTrainee Biotech Data Science Jobs

Trainee Biotech Data Science information

See salary details

$14

$33

$56

How much do trainee biotech data science jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for trainee biotech data science in the United States is $33.07, according to ZipRecruiter salary data. Most workers in this role earn between $24.52 and $39.18 per hour, depending on experience, location, and employer.

What is the difference between Trainee Biotech Data Science vs Junior Biotech Data Analyst?

AspectTrainee Biotech Data ScienceJunior Biotech Data Analyst
Required CredentialsBachelor's in biotech, data science, or related fieldBachelor's in biotech, life sciences, or related field
Work EnvironmentResearch labs, biotech companies, data-focused projectsBiotech firms, research institutions, data reporting
Industry UsageData science, machine learning, bioinformaticsData analysis, reporting, data management
Common Search/ComparisonYesYes

The Trainee Biotech Data Science role focuses on applying data science and bioinformatics techniques within biotech settings, often involving machine learning and programming. In contrast, a Junior Biotech Data Analyst primarily handles data reporting and basic analysis. Both roles require a background in biotech or related fields, but the data science trainee emphasizes advanced data modeling, while the analyst concentrates on data interpretation and reporting.

What cities are hiring for Trainee Biotech Data Science jobs? Cities with the most Trainee 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 Trainee Biotech Data Science jobs? States with the most job openings for Trainee Biotech Data Science jobs include:
What job categories do people searching Trainee Biotech Data Science jobs look for? The top searched job categories for Trainee Biotech Data Science jobs are:
Trainee Biotech Data Science jobs near you
Infographic showing various Trainee Biotech Data Science job openings in the United States as of May 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 96% Physical, 2% Hybrid, and 2% Remote job distribution, with an average salary of $68,795 per year, or $33.1 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

Apply