Full Time Python Bioinformatics Jobs in St Louis, MO

As of Jul 14, 2026, the average yearly pay for full time python bioinformatics in St. Louis, MO is $111,910.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,200.00 and $154,600.00 per year, depending on experience, location, and employer.

As a Full Time Python Bioinformatics professional, you can expect to work on projects such as developing data analysis pipelines for genomic sequencing, creating visualization tools for biological datasets, or automating workflows for large-scale biological experiments. Collaboration is a key aspect of the role; you will frequently work alongside biologists, data scientists, and software engineers to ensure that computational solutions address scientific questions effectively. Regular meetings to discuss project goals, code reviews, and joint troubleshooting sessions are common, fostering a dynamic and interdisciplinary work environment.

To thrive as a Full Time Python Bioinformatics professional, you need a solid background in biology or bioinformatics, strong Python programming skills, and typically a degree in a related field such as bioinformatics, computer science, or computational biology. Familiarity with bioinformatics tools (like Biopython), databases (such as NCBI or Ensembl), and version control systems (like Git) is commonly expected. Critical thinking, problem-solving ability, and effective communication are important soft skills for interpreting complex biological data and collaborating with interdisciplinary teams. These skills and qualifications are essential for developing accurate analysis pipelines and driving meaningful research outcomes in the fast-evolving field of bioinformatics.

A Full Time Python Bioinformatics professional uses Python programming to analyze and interpret biological data, such as DNA, RNA, or protein sequences. They develop scripts and software tools to handle large datasets, automate workflows, and perform statistical analyses to support research in areas like genomics and drug discovery. Their work often involves collaborating with biologists and other scientists to translate complex biological questions into computational solutions.