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Bioinformatics Data Engineer Jobs in Wisconsin (NOW HIRING)

... bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

... bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

... bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

... bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

Applicants with Master's Degree are highly preferred and given first consideration; focus in Bioinformatics, Clinical Informatics, Data Science, Data Engineering, or related field preferred. How to ...

Master's (+5 years experience) or PhD (+2 years experience) in Data Science, Biostatistics, Bioinformatics, Biomedical Engineering or related field * Strong background in quantitative analysis and ...

Master's (+5 years experience) or PhD (+2 years experience) in Data Science, Biostatistics, Bioinformatics, Biomedical Engineering or related field * Strong background in quantitative analysis and ...

Senior Data Scientist

Madison, WI · On-site

$120 - $170/hr

Master's (+5 years experience) or PhD (+2 years experience) in Data Science, Biostatistics, Bioinformatics, Biomedical Engineering or related field * Strong background in quantitative analysis and ...

WI · On-site

$79.93 - $125.60/hr

We are looking for an experienced Senior Research Software Engineer to lead the design and ... You hold a Master degree in bioinformatics, computational biology, genomics, computer science, data ...

... bioinformatics, molecular modeling, or programming is desirable but not required. Experience with Python, Linux, high-performance computing (HPC) environments, molecular visualization, or data ...

Bioinformatics Data Engineer information

What is a bioinformatics data engineer?

A Bioinformatics Data Engineer is a professional who designs, develops, and maintains data infrastructure for managing and analyzing large-scale biological data, such as genomics or proteomics datasets. They build pipelines and tools to process, store, and retrieve complex biological information efficiently. Their work enables researchers and scientists to access and interpret data for discoveries in fields like medicine, genetics, and biotechnology. Often, they collaborate closely with bioinformaticians, data scientists, and software engineers to support research initiatives.

How do bioinformatics data engineers typically collaborate with researchers and other teams in a biomedical organization?

Bioinformatics Data Engineers often work closely with biologists, data scientists, and software engineers to ensure the effective collection, processing, and analysis of complex biological data. They regularly participate in cross-functional meetings to understand research goals, develop data pipelines, and troubleshoot data-related issues. Collaboration is essential, as engineers must translate scientific requirements into technical solutions, provide data access and visualization tools, and support researchers in extracting meaningful insights from large datasets. This teamwork fosters a dynamic environment where communication and adaptability are key.

What are the key skills and qualifications needed to thrive as a bioinformatics data engineer, and why are they important?

To thrive as a Bioinformatics Data Engineer, you need a strong background in computer science, biology, and statistics, often supported by a relevant degree and experience in data engineering. Proficiency with programming languages (such as Python, R, or SQL), bioinformatics tools, cloud platforms, and big data frameworks (like Hadoop or Spark) is typically required. Strong problem-solving, collaboration, and communication skills help you work effectively across interdisciplinary teams and convey complex findings. These skills ensure accurate analysis, efficient data pipeline development, and meaningful insights that advance biological research and healthcare solutions.

What is the difference between Bioinformatics Data Engineer vs Bioinformatics Analyst?

AspectBioinformatics Data EngineerBioinformatics Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computer Science, or related fields; programming skillsBachelor's or Master's in Bioinformatics, Biology, or related fields; data analysis skills
Work EnvironmentData pipelines, database management, software developmentData interpretation, report generation, biological data analysis
Employer & Industry UsageBiotech companies, research labs, pharmaResearch institutions, healthcare, biotech
Common Search & ComparisonFocuses on data infrastructure and pipelinesFocuses on biological data interpretation

The main difference between a Bioinformatics Data Engineer and a Bioinformatics Analyst lies in their focus areas. Data Engineers build and maintain data pipelines and infrastructure, while Analysts interpret biological data to generate insights. Both roles require strong bioinformatics knowledge, but Data Engineers emphasize programming and data management, whereas Analysts focus on biological interpretation and reporting.

What are popular job titles related to Bioinformatics Data Engineer jobs in Wisconsin?

For Bioinformatics Data Engineer jobs in Wisconsin, the most frequently searched job titles are:

What cities in Wisconsin are hiring for Bioinformatics Data Engineer jobs?

Cities in Wisconsin with the most Bioinformatics Data Engineer job openings:

Bioinformatics Software Engineer

micro1 AI

Green Bay, WI • Remote

$80 - $110/hr

Part-time

Posted 20 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.