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Bioinformatics Data Analyst Jobs in Indiana (NOW HIRING)

... bioinformatics side of NGS utilizing advanced computational methods to analyze the results obtained from NGS assays. The incumbent should have experience with developing primer/probe sets, data ...

Research Biostatistician

Fort Wayne, IN ยท On-site

$26.85 - $40.27/hr

... analyze data, interpret findings, and support the publication of meaningful research. You'll work across a diverse range of healthcare research areas, including clinical, bioinformatics ...

New

Senior Analyst - Discovery Research

Indianapolis, IN ยท On-site

$110K - $111K/yr

... data and advance antibody discovery programs. Your Responsibilities * Execute antibody discovery ... Experience with bioinformatic analysisand selection of antibodies and other proteins.

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Bioinformatics Data Analyst information

See Indiana salary details

$6

$43

$78

How much do bioinformatics data analyst jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for bioinformatics data analyst in Indiana is $43.60, according to ZipRecruiter salary data. Most workers in this role earn between $34.33 and $46.68 per hour, depending on experience, location, and employer.

What is a bioinformatics data analyst?

Bioinformatics Data Analysts are professionals who use computational tools and methods to analyze biological data, such as genomic sequences or protein structures. They work at the intersection of biology, computer science, and statistics to interpret complex datasets and draw meaningful insights for research or clinical applications. Their work supports areas like drug discovery, personalized medicine, and evolutionary biology. Typically, they collaborate with biologists, software engineers, and statisticians to solve complex biological problems. Strong analytical skills and proficiency with data analysis software are essential for this role.

How do bioinformatics data analysts collaborate with researchers and other team members?

Bioinformatics Data Analysts often work closely with biologists, clinicians, and software engineers, acting as a bridge between experimental research and computational analysis. Collaboration usually involves interpreting experimental data, discussing analytical approaches, and presenting findings in a way that's accessible to non-technical stakeholders. Regular team meetings and project updates are common, and strong communication skills are essential for translating complex data insights into actionable information for the broader research team. This multidisciplinary teamwork fosters innovation and ensures that analyses align with the goals of larger research projects.

What are the key skills and qualifications needed to thrive as a bioinformatics data analyst?

To thrive as a Bioinformatics Data Analyst, a solid background in biology, statistics, and programming (often with a degree in bioinformatics, computational biology, or a related field) is essential. Proficiency with tools such as R, Python, SQL, and bioinformatics software like BLAST or Bioconductor, as well as experience with large datasets and relevant certifications, is typically required. Strong analytical thinking, attention to detail, and effective communication skills help analysts interpret complex data and collaborate with interdisciplinary teams. These skills ensure accurate data analysis, meaningful biological insights, and successful project outcomes in research or clinical settings.

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

AspectBioinformatics Data AnalystBioinformatics Scientist
Required CredentialsBachelor's or Master's in Bioinformatics, Biology, or related fieldsMaster's or PhD in Bioinformatics, Computational Biology, or related fields
Work EnvironmentData analysis teams, research labs, healthcare settingsResearch projects, development of algorithms, scientific publications
Employer & Industry UsageBiotech companies, healthcare institutions, research organizationsAcademic institutions, biotech firms, pharmaceutical companies
Common Search & ComparisonOften compared for data analysis roles in bioinformaticsMore research-focused, involved in algorithm development

Bioinformatics Data Analysts primarily focus on analyzing biological data using existing tools, while Bioinformatics Scientists develop new algorithms and conduct research. Both roles require strong computational skills, but the Scientist role typically involves more advanced research and innovation.

What cities in Indiana are hiring for Bioinformatics Data Analyst jobs?

Cities in Indiana with the most Bioinformatics Data Analyst job openings:

Infographic showing various Bioinformatics Data Analyst job openings in Indiana as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $90,692 per year, or $43.6 per hour.

Senior AI Engineer - Bioinformatics

Marlabs

Indianapolis, IN โ€ข On-site

Full-time

Re-posted 9 days ago


Job description

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Senior AI Engineer - Bioinformatics to join our innovative and dynamic team.
Senior AI Engineer - Bioinformatics | About You
As a Senior AI Engineer - Bioinformatics, you are responsible for building modern, data-driven web applications that enable scientists and researchers to interact with complex datasets intuitively and efficiently. You enjoy working across the entire stack, from designing backend services and APIs to crafting responsive, elegant frontends. You thrive in environments where you collaborate closely with UX designers, scientists, and engineering partners to turn ideas into high-impact tools. You value clean architecture, reusable components, automated testing, and strong engineering best practices. You are energized by creating user experiences that simplify scientific workflows and make large-scale data accessible and actionable.
Senior AI Engineer - Bioinformatics | Day-to-Day
  • Design, develop, and support scalable full-stack applications and AI-powered solutions using Python and modern development technologies.
  • Build and integrate Generative AI capabilities using LLM platforms such as OpenAI, Azure OpenAI, and Anthropic, including prompt engineering and context management.
  • Develop agentic workflows, tool integrations, and function-calling capabilities to automate complex business processes and enhance user experiences.
  • Integrate enterprise applications with platforms such as Microsoft 365, SharePoint, Microsoft Graph, ServiceNow, Jira, and Confluence through secure APIs.
  • Implement secure authentication, authorization, and secrets management practices while ensuring compliance with enterprise security standards.
  • Collaborate with cross-functional teams to deliver, deploy, and continuously improve applications through CI/CD pipelines, containerization, and modern DevOps practices.

Senior AI Engineer - Bioinformatics | Skills & Experience
  • 7+ years of experience in full-stack application development within enterprise or technology-driven environments, with strong proficiency in Python.
  • Hands-on experience building AI and Generative AI solutions, including LLM API integrations, prompt engineering, token management, and conversational AI applications.
  • Strong experience with enterprise integrations, including Microsoft 365, Microsoft Graph, SharePoint, ServiceNow, Jira, Confluence, and REST APIs.
  • Expertise in secure application development, including SSO integrations (SAML, OAuth2, OIDC), API gateways, middleware, and secrets management best practices.
  • Experience with modern DevOps and cloud-native development, including containerization, CI/CD pipelines, deployment automation, and application lifecycle management.