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Entry Level Bioinformatics Data Scientist Jobs in Iowa

Pwc

AI & GenAI Data Scientist - Manager

Des Moines, IA · On-site

$99K - $232K/yr

... GenAI Data Scientist - Manager, you will play a pivotal role in transforming raw data into ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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micro1 AI

Bioinformatics Software Engineer

Davenport, IA · Remote

$80 - $110/hr

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

micro1 AI

Bioinformatics Software Engineer

Des Moines, IA · Remote

$80 - $110/hr

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

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Entry Level Bioinformatics Data Scientist information

What does an entry level bioinformatics data scientist do?

An Entry Level Bioinformatics Data Scientist applies computational and statistical techniques to analyze biological data, such as DNA sequences or gene expression profiles. They work with large datasets to identify patterns, generate insights, and contribute to research in fields like genomics, drug discovery, or personalized medicine. Their tasks often include data cleaning, developing algorithms, running analyses, and visualizing results for scientific teams. They typically collaborate with biologists, statisticians, and software engineers to solve complex biological problems.

What are the key skills and qualifications needed to thrive as an entry level bioinformatics data scientist?

To thrive as an Entry Level Bioinformatics Data Scientist, you need a solid background in biology, statistics, and computer science, often supported by a relevant degree in bioinformatics or a related field. Familiarity with programming languages such as Python or R, experience with bioinformatics tools like BLAST or Bioconductor, and knowledge of data analysis platforms are typically required. Strong problem-solving skills, attention to detail, and effective communication are important soft skills for interpreting complex data and collaborating with multidisciplinary teams. These skills and qualifications are essential for accurately analyzing biological data, generating meaningful insights, and contributing to research or clinical projects.

What are some typical challenges faced by entry level bioinformatics data scientists during their first year on the job?

Entry level bioinformatics data scientists often encounter challenges such as adapting to complex biological datasets, learning to use specialized bioinformatics tools, and understanding the nuances of interdisciplinary collaboration with biologists and clinicians. Balancing data analysis with ongoing skill development in programming and statistics is another common hurdle. However, most teams provide mentorship and training to help new hires acclimate and build confidence in tackling real-world research problems.

What is the difference between Entry Level Bioinformatics Data Scientist vs Entry Level Bioinformatics Analyst?

AspectEntry Level Bioinformatics Data ScientistEntry Level Bioinformatics Analyst
Required CredentialsBachelor's in Bioinformatics, Biology, Computer Science; some roles prefer internships or certificationsBachelor's in Bioinformatics, Biology, or related field; similar educational background
Work EnvironmentResearch labs, biotech companies, healthcare institutions, academic settingsResearch labs, healthcare, biotech firms, academic institutions
Employer & Industry UsageUsed in biotech, pharma, healthcare, research institutionsCommon in research, healthcare, biotech sectors

Both roles require similar educational backgrounds and work environments, focusing on analyzing biological data. The main difference is that a Bioinformatics Data Scientist often involves more advanced data modeling, machine learning, and statistical analysis, whereas a Bioinformatics Analyst typically concentrates on data processing, visualization, and reporting. Entry Level Bioinformatics Data Scientists tend to handle more complex computational tasks, but both roles serve essential functions in biological research and industry applications.

What are popular job titles related to Entry Level Bioinformatics Data Scientist jobs in Iowa?

For Entry Level Bioinformatics Data Scientist jobs in Iowa, the most frequently searched job titles are:

What job categories do people searching Entry Level Bioinformatics Data Scientist jobs in Iowa look for?

The top searched job categories for Entry Level Bioinformatics Data Scientist jobs in Iowa are:

Entry Level Bioinformatics Data Scientist jobs near you
Infographic showing various Entry Level Bioinformatics Data Scientist job openings in Iowa as of August 2026, with employment types broken down into 33% Full Time, and 67% Part Time. Highlights an 67% In-person, and 33% Remote job distribution.

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Davenport, IA • Remote

$80 - $110/hr

Part-time

Posted 26 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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