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Bioinformatics Programmer Analyst Jobs in Tennessee

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Bioinformatics Programmer Analyst information

What is a bioinformatics programmer analyst?

A Bioinformatics Programmer Analyst is a professional who combines knowledge of biology, computer science, and statistics to manage, analyze, and interpret complex biological data, often using programming and software development skills. They typically work with large datasets such as genomic sequences, gene expression profiles, or proteomics data to derive meaningful insights for research or clinical applications. Their role often involves developing software tools, writing scripts for data analysis, and collaborating with biologists and other scientists to solve research problems. Bioinformatics Programmer Analysts are essential in fields like genomics, pharmaceutical research, and personalized medicine.

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

To thrive as a Bioinformatics Programmer Analyst, you need strong programming skills (such as Python, R, or Perl), a background in biology or bioinformatics, and typically a bachelor's or master's degree in a relevant field. Familiarity with bioinformatics tools, databases (like NCBI, Ensembl), and experience using Linux environments and version control systems (like Git) are essential. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for interpreting data and collaborating with research teams. These competencies are vital for accurately analyzing biological data and delivering actionable insights in research or clinical settings.

What are some common challenges faced by bioinformatics programmer analysts when integrating new data types into existing pipelines?

Bioinformatics Programmer Analysts often encounter challenges such as data heterogeneity, inconsistent formats, and varying quality when integrating new data types into established analysis pipelines. Addressing these issues requires careful data preprocessing, validation, and sometimes developing custom scripts or modules to ensure compatibility. Collaboration with biologists and data scientists is essential to understand the context of the new data and to tailor solutions that maintain the reliability and reproducibility of results. Staying adaptable and up-to-date with evolving bioinformatics tools and standards also helps in overcoming these integration challenges.

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

AspectBioinformatics Programmer AnalystBioinformatics Data Scientist
Required CredentialsBachelor's in Bioinformatics, Computer Science, or related field; programming skillsBachelor's or Master's in Bioinformatics, Data Science, or related; strong statistical and programming skills
Work EnvironmentResearch labs, biotech companies, healthcare institutionsResearch institutions, biotech firms, healthcare analytics
Employer & Industry UsageUsed in biotech, pharma, healthcare for data analysis and software development

The Bioinformatics Programmer Analyst primarily focuses on developing software tools and analyzing biological data using programming skills. In contrast, the Bioinformatics Data Scientist emphasizes statistical analysis and data modeling to interpret complex biological datasets. Both roles require strong programming knowledge and are common in biotech and healthcare industries, but their core responsibilities differ in software development versus data analysis.

What are popular job titles related to Bioinformatics Programmer Analyst jobs in Tennessee?

For Bioinformatics Programmer Analyst jobs in Tennessee, the most frequently searched job titles are:

What job categories do people searching Bioinformatics Programmer Analyst jobs in Tennessee look for?

The top searched job categories for Bioinformatics Programmer Analyst jobs in Tennessee are:

What cities in Tennessee are hiring for Bioinformatics Programmer Analyst jobs?

Cities in Tennessee with the most Bioinformatics Programmer Analyst job openings:

Infographic showing various Bioinformatics Programmer Analyst job openings in Tennessee as of August 2026, with employment types broken down into 1% Internship, 81% Full Time, 11% Part Time, 1% Temporary, and 6% Contract. Highlights an 80% Physical, 8% Hybrid, and 12% Remote job distribution.

Sr Computational Research Scientist- MA's Lab

St. Jude Children's Research Hospital

Memphis, TN • On-site

$95K - $121K/yr

Full-time

Re-posted 21 days ago


St. Jude Children's Research Hospital rating

8.6

Company rating: 8.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

43rd of 1,060 rated hospitals


Job description

Join our Team!
The Ma laboratory in the Department of Computational Biology is seeking an experienced Senior Computational Research Scientist for the Pediatric Cancer Dependency (PedDep) project, a joint initiative between St. Jude, Dana Farber Cancer Institute, and the Broad Institute.
With vast knowledge accumulated from patient tumor data, we are now characterizing cell models (cell lines and PDX models) for childhood cancers to discover novel vulnerabilities that can lead to new therapeutic targets. In this role you will analyze the genomics data from >1,000 cancer cell models to identify their driver alterations and investigate the representativeness of cell models against the mutations observed in primary tumors. You will also study the similarities and differences of driver alterations between pediatric and adult cancers. Published studies from external and internal cohorts will be compiled for the comparison. In addition to the extensive internal tools we have developed, you will develop novel tools during the investigation to generate novel analyses and to integrate new data types. You are expected to present findings in regular internal/external forums and to draft figures/manuscripts with the help of the PI and the team.
Highly motivated candidates with an MD/PhD in molecular biology, computational biology, computer science, or a closely related field are encouraged to apply. The candidate would ideally have ample experience with genome and transcriptome sequencing data analysis, in particular mutation detection and functional interpretation, as well as extensive computational skills to accurately and efficiently handle large amounts of data. Candidates should be scientifically curious, rigorous, and capable of working independently.
Position Responsibilities:
  • Lead computationally focused scientific research projects with little supervision from their PI.
  • Initiate and execute research strategies in partnership with the Principal Investigator, collaborator, and/or more experienced scientists.
  • Explore, identify, and propose adoption of relevant emerging scientific and technical trends in computational research; develop new methods, techniques, and procedures.
  • Identify, process, organize, interpret, review, and report relevant data; generate hypotheses to predict future implications based on the critical evaluation of these data.
  • Direct/monitor data collection.
  • Present research both internally and externally to multi-disciplinary audiences; draft complex manuscripts.
  • Provide ongoing instruction and guidance to junior-level staff and train as needed.
  • Perform other duties as assigned to meet the goals and objectives of the department and institution.
  • Maintains regular and predictable attendance.

Minimum Education and/or Training:
  • Training in Bioinformatics, Molecular Biology, Computer Science, or related fields.

Minimum Experience:
  • Bachelor's degree and 7+ years of relevant experience.

Experience Exception:
  • Master's degree and 5+ years of relevant experience (OR) PhD with 2+ years of relevant experience.
  • Rough criteria for this position based on publication output: 1-2 first author papers IF > 10 (or equivalent contribution to other research outputs).
  • Substantial experience in own technical area including advanced research techniques.
  • Experience leading complex research studies in a technical capacity preferred.
  • Experience training and guiding early-career researchers preferred.
  • Proven performance in earlier role/ comparable role.

Special Skills, Knowledge, and Abilities:
Ideal candidate should have:
  • Strong knowledge in molecular biology, genetics, genomics and statistics.
  • Next generation sequencing: variant calling; IGV-based variant inspection; whole-genome/exome analysis for mutations including copy number, loss of heterozygosity, structural variation, SNV/Indel; RNAseq based fusion analysis; bam/fastq operations including mapping and basic quality control; variant functional interpretation using data collected from patient cohort and molecular biology and genetics principles.
  • Programming: [Python or Perl or C/C++] and R
  • Operating system: High performance computing system, bash scripting
  • Office: Microsoft Excel/Word/PowerPoint

Preferred:
  • Adobe Illustrator (no Photoshop)

About the lab and St. Jude:
Recognized for state-of-the-art computational infrastructure, well-established analytical pipelines, and deep genomic analysis expertise, St. Jude offers a work environment where you will directly impact the care of pediatric cancer patients.
The Ma laboratory has extensive experience in the analysis of whole genome, exome, and transcriptome data to detect mutations responsible for tumorigenesis and therapeutic resistance using primary tumor data. We are particularly experienced in developing novel analytical methods for DNA/RNA sequencing analysis, including cancer-early detection where signal-to-noise ratio can be very low and present as a significant challenge for the community, and the general patterns of cancer driver mutations with the aim of understanding why cancer happens. We also pay special attention to novel biotechnologies including long read sequencing to solve challenging problems related to childhood cancers.
The Department of Computational Biology provides access to high-performance computing clusters, a cloud computing environment, innovative visualization tools, highly automated analytical pipelines, and mentorship from faculty scientists with experience in data analysis, data management, and delivery of high-quality results for competitive projects. We encourage first-author, high-profile publications to share this element of discovery. Take the first step to joining our team by applying now!
Relevant Papers:
Ma X, Liu Y, Liu Y, Alexandrov LB, Edmonson MN, Gawad C, Zhou X, Li Y, Rusch MC, Easton J, Huether R, Gonzalez-Pena V, Wilkinson MR, Hermida LC, Davis S, Sioson E, Pounds S, Cao X, Ries RE, Wang Z, Chen X, Dong L, Diskin SJ, Smith MA, Guidry Auvil JM, Meltzer PS, Lau CC, Perlman EJ, Maris JM, Meshinchi S, Hunger SP, Gerhard DS, Zhang J. Pan-cancer genome and transcriptome analyses of 1,699 paediatric leukaemias and solid tumours. Nature. 2018 Mar 15;555(7696):371-376. doi: 10.1038/nature25795. Epub 2018 Feb 28. PMID: 29489755; PubMed Central PMCID: PMC5854542.
Ma X*#, Shao Y, Tian L, Flasch DA, Mulder HL, Edmonson MN, Liu Y, Chen X, Newman S, Nakitandwe J, Li Y, Li B, Shen S, Wang Z, Shurtleff S, Robison LL, Levy S, Easton J, Zhang J. Analysis of error profiles in deep next-generation sequencing data. Genome Biol. 2019 Mar 14;20(1):50. doi: 10.1186/s13059-019-1659-6. PMID: 30867008; PubMed Central PMCID: PMC6417284.
Li B, Brady SW, Ma X*, Shen S, Zhang Y, Li Y, Szlachta K, Dong L, Liu Y, Yang F, Wang N, Flasch DA, Myers MA, Mulder HL, Ding L, Liu Y, Tian L, Hagiwara K, Xu K, Zhou X, Sioson E, Wang T, Yang L, Zhao J, Zhang H, Shao Y, Sun H, Sun L, Cai J, Sun HY, Lin TN, Du L, Li H, Rusch M, Edmonson MN, Easton J, Zhu X, Zhang J, Cheng C, Raphael BJ, Tang J, Downing JR, Alexandrov LB, Zhou BS, Pui CH, Yang JJ, Zhang J. Therapy-induced mutations drive the genomic landscape of relapsed acute lymphoblastic leukemia. Blood. 2020 Jan 2;135(1):41-55. doi: 10.1182/blood.2019002220. PMID: 31697823; PubMed Central PMCID: PMC6940198.
Davis EM, Sun Y, Liu YL, Kolekar P, Shao Y, Szlachta K, Mulder HL, Ren DR, Rice SV, Wang Z, Nakitandwe J, Gout AM, Shaner B, Hall S, Robison LL, Pounds S, Klco JM, Easton J, Ma X#. SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data. Genome Biol. 2021 Jan 25;22(1):37. doi: 10.1186/s13059-020-02254-2. PMID: 33487172
Liu Y, Klein J, Bajpai R, Dong L, Tran Q, Kolekar P, Smith JL, Ries RE, Huang BJ, Wang YC, Alonzo TA, Tian L, Mulder HL, Shaw TI, Ma J, Walsh MP, Song G, Westover T, Autry RJ, Gout AM, Wheeler DA, Wan S, Wu G, Yang JJ, Evans WE, Loh M, Easton J, Zhang J, Klco JM, Meshinchi S, Brown PA, Pruett-Miller SM, Ma X#. Etiology of oncogenic fusions in 5,190 childhood cancers and its clinical and therapeutic implication. Nat Commun. 2023 Apr 5;14(1):1739. doi: 10.1038/s41467-023-37438-4. PMID: 37019972
Kolekar P, Balagopal V, Dong L, Liu Y, Foy S, Tran Q, Mulder H, Huskey A, Plyler E, Liang Z, Ma J, Nakitandwe J, Gu J, Namwanje M, Maciaszek J, Payne-Turner D, Mallampati S, Wang L, Easton J, Klco J, Ma X#. SJPedPanel: A Pan-Cancer Gene Panel for Childhood Malignancies to Enhance Cancer Monitoring and Early Detection. Clin Cancer Res. 2024 Sep 13;30(18):4100-4114. doi: 10.1158/1078-0432.CCR-24-1063. PMID: 39047169
Shao Y, Tran Q, Feng Y, Kolekar P, Liu Y, Liang Z, Fan L, McBride A, Jones T, Cameron A, Mulder H, Ji L, Huang BJ, Klco JM, Meshinchi S, Zhang J, Carroll WL, Loh ML, Easton J, Brown PA, Ma X#. Analysis of error profiles of indels and structural variants in deep-sequencing data. Cell Genom. 2026 Feb 11;6(2):101082. doi: 10.1016/j.xgen.2025.101082. Epub 2025 Dec 2. PubMed PMID: 41338220; PubMed Central PMCID: PMC12903382.
Liu Y, Ju B, Dong L, Loyd M, Brady SW, Ries R, Feng Y, Mulder H, Plyler E, Deardorff C, McBride A, Jones T, Eckert A, Kolekar P, Fan L, Li H, Briviba M, Zhao H, Bennett D, Neale G, Chang TC, Chen W, Pounds S, Wu G, Mullighan C, Geeleher P, Ji L, Yang JJ, Meshinchi S, Brown PA, Carroll WL, Zhang J, Loh ML, Easton J, Ma X#. Uncovering the genomic complexity of PAX5 intragenic tandem multiplication via long-read and short-read sequencing. Blood. 2026 Mar 26;147(13):1498-1502. doi: 10.1182/blood.2025031289. PubMed PMID: 41587071.
Compensation
In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a reasonable estimate of the compensation range for this role. This is an estimate offered in good faith and a specific salary offer takes into account factors that are considered in making compensation decisions including but not limited to skill sets, experience and training, licensure and certifications, and other business and organizational needs. It is not typical for an individual to be hired at or near the top of the salary range and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current salary range is $104,000 - $186,160 per year for the role of Sr Computational Research Scientist- MA's Lab.
Explore our exceptional benefits!
St. Jude is an Equal Opportunity Employer
No Search Firms
St. Jude Children's Research Hospital does not accept unsolicited assistance from search firms for employment opportunities. Please do not call or email. All resumes submitted by search firms to any employee or other representative at St. Jude via email, the internet or in any form and/or method without a valid written search agreement in place and approved by HR will result in no fee being paid in the event the candidate is hired by St. Jude.

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