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Part Time Biological Data Analyst information

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$34K

$82.6K

$136K

How much do part time biological data analyst jobs pay per year?

As of Aug 26, 2026, the average yearly pay for part time biological data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What does a part time biological data analyst do?

A Part Time Biological Data Analyst works with biological data to help researchers or organizations interpret complex biological information. Their duties typically include collecting, cleaning, and analyzing data from experiments or studies, often using statistical software and programming languages like R or Python. They may work on projects related to genomics, ecology, clinical trials, or other biology-related fields, providing insights that support scientific research or decision making. Since the position is part-time, the analyst may work flexible hours or on a project basis.

What are the key skills and qualifications needed to thrive as a part time biological data analyst, and why are they important?

To thrive as a Part Time Biological Data Analyst, you need a strong background in biology or bioinformatics, statistical analysis, and data management, typically supported by a related degree. Familiarity with tools such as R, Python, SQL, and bioinformatics databases, as well as experience with data visualization software, is commonly required. Attention to detail, critical thinking, and effective communication are soft skills that help analysts accurately interpret data and collaborate with research teams. These skills and qualifications are essential for drawing meaningful insights from complex biological datasets and supporting sound scientific conclusions.

What are some common challenges faced by part time biological data analysts, and how can they manage their workload effectively?

Part-time biological data analysts often face the challenge of managing complex datasets and research timelines within limited working hours. Balancing multiple projects or shifting priorities can make time management especially important. Effective communication with team members and clear documentation of work progress are essential to ensure smooth collaboration and data continuity. Utilizing project management tools and setting realistic goals for each shift can help part-time analysts stay organized and productive.

What is the difference between Part Time Biological Data Analyst vs Part Time Biological Research Assistant?

AspectPart Time Biological Data AnalystPart Time Biological Research Assistant
Required CredentialsBachelor's in Biology, Data Analysis, or related field; proficiency in statistical softwareBachelor's in Biology or related field; laboratory skills often emphasized
Work EnvironmentData analysis in office or remote settingsLaboratory or field research settings
Employer & Industry UsageResearch institutions, biotech companies, environmental agenciesUniversities, research labs, environmental organizations
Common Search & ComparisonYesYes

The main difference is that Part Time Biological Data Analysts focus on analyzing biological data using software tools, while Part Time Biological Research Assistants typically assist with laboratory or field research activities. Both roles require a background in biology, but the Data Analyst emphasizes data skills, whereas the Research Assistant emphasizes hands-on lab work.

More about Part Time Biological Data Analyst jobs

What are the most commonly searched types of Biological Data Analyst jobs?

The most popular types of Biological Data Analyst jobs are:

What job categories do people searching Part Time Biological Data Analyst jobs look for?

The top searched job categories for Part Time Biological Data Analyst jobs are:

Part Time Biological Data Analyst jobs near you
Infographic showing various Part Time Biological Data Analyst job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Data selection and quality evaluation for biological foundation models

Inceptive

Palo Alto, CA

Part-time

Re-posted 10 days ago

Job description

At Inceptive, you will help pioneer the next generation of AI-designed drugs, with the potential to positively impact billions of people, as part of a collaborative, antedisciplinary team.

We advance the state of the art in molecular design by training large-scale foundation models that enable cutting-edge generative approaches. Those models depend on rich, high-quality experimental data that captures biological function. Progress requires not only building better models, but also designing better experiments, understanding measurement systems, and generating datasets that faithfully represent underlying biology.

You will collaborate closely with biologists and machine learning researchers to design, analyze, and improve the experiments that power our models. You will help determine what data should be generated, how experiments should be structured, how measurement artifacts can be identified, and how biological insights can be translated into scalable data generation strategies.

Your Mission, should you choose to accept it

  • Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise
  • Develop statistical and computational approaches to characterize assay quality, reproducibility, and sources of experimental variation
  • Identify and investigate sources of bias and measurement artifacts in biological datasets
  • Design and analyze large-scale biological experiments that generate training and evaluation data for machine learning models
  • Partner with experimental scientists to improve assay design, controls, and data collection strategies
  • Collaborate with machine learning researchers to understand how experimental design decisions impact model training and evaluation
  • Analyze, visualize, and communicate findings to support decision-making across scientific and engineering teams

Qualifications

  • PhD in computational biology, systems biology, genomics, bioengineering, biostatistics, biophysics, or a related quantitative discipline, or equivalent practical experience
  • Demonstrated track record of analyzing complex biological datasets and translating computational insights into experimental validation or new data collection
  • Strong foundation in experimental design, statistical analysis, and quantitative reasoning
  • Deep understanding of sources of experimental variability, batch effects, and assay artifacts in biological data
  • Capable programmer in Python and common scientific computing libraries
  • Excellent written and verbal communication skills, including the ability to communicate effectively across computational and experimental disciplines
  • Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET
  • Readiness to travel several times a year for company retreats and business events
  • We value the benefits of in-person collaboration and expect candidates to primarily work from our office locations

Preferred technical skills

  • 3+ years of post-PhD experience in computational biology, biostatistics, or a related field
  • Experience connecting experimental outcomes to machine learning model development and evaluation

Compensation

$135K - $240K + Bonus + Equity

Apply