Photo: Steve Jurvetson (CC BY 2.0)
Job description
Much of the work involves building and mining large genomic or proteomic databases, looking for patterns that point toward new biological insight. Bioinformatics scientists often consult directly with researchers to figure out which computational strategy fits a given problem, then may direct a team of technicians or IT staff applying those tools day to day. Staying current means regularly reading new literature and attending conferences, since the underlying instrumentation and software change quickly. The work is precise and highly structured, and most in the field hold a master's or PhD in bioinformatics or a closely related field.
Pros
- High upside earning potential, up to $168k for senior research scientists
- Sits at the intersection of biology and computing, appealing to those who like both
- Relatively strong demand with 4,800 positions nationwide, more accessible than narrower research fields
Cons
- Above-average hours, expect more than a standard 40-hour work week
- Slower than average projected job growth (1.2%) compared to other science fields
- Requires a master's or PhD in a specialized, still-developing interdisciplinary field
A typical day
The sequencing run finished overnight: 400 gigabytes of reads from tumor samples, and the morning goes to quality control before anything else — garbage in is the field's cardinal sin. The pipeline hums on the computing cluster while the scientist writes the analysis that matters: differential expression between responders and non-responders to a therapy, statistical rigor guarding against the false discoveries that plague genomics. A noon meeting with wet-lab biologists is the job's essential translation act — they ask biological questions, the scientist reframes them as computable ones and pushes back where the sample size can't support the wish. Afternoon holds code review of a new variant-calling workflow, a manuscript figure polished, and a mentoring session with an intern whose script works but wouldn't survive a second dataset.
Tasks at the job
- Communicate research results through conference presentations, scientific publications, or project reports.
- Consult with researchers to analyze problems, recommend technology-based solutions, or determine computational strategies.
- Keep abreast of new biochemistries, instrumentation, or software by reading scientific literature and attending professional conferences.
- Develop data models and databases.
- Manipulate publicly accessible, commercial, or proprietary genomic, proteomic, or post-genomic databases.
- Direct the work of technicians and information technology staff applying bioinformatics tools or applications in areas such as proteomics, transcriptomics, metabolomics, or clinical bioinformatics.
Workplace & working conditions
Work happens indoors in a climate-controlled setting, and most of the day is spent sitting at a desk.
There's a regular, moderate amount of time pressure, and you're expected to exercise significant independent judgment day to day. Precision and accuracy are essential to the work, and the work is highly structured, following set procedures. Almost all of the work is done as part of a team.
Education necessary or common
Master's degree or Doctor of Philosophy (PhD) in bioinformatics, computational biology, or a related field
Common college majors
Career path
Related fields
Courses to take
- AP Biology — genetics and molecular biology are the domain
- AP Computer Science A — code is the daily instrument
- AP Statistics — the discipline that separates discoveries from noise
- AP Calculus BC
- AP Chemistry
Clubs, activities & competitions
- Science Olympiad (Codebusters, Protein Modeling, Disease Detectives)
- Coding club or competitive programming
- Science fair with a computational biology project
- Math team
First steps you can take now
- Learn Python, then work through a free bioinformatics exercise set (Rosalind.info is built exactly for this and free)
- Pull a real dataset from NCBI's public archives and compute something simple about it
- Do a science fair project analyzing public genomic or epidemiological data
- Watch a lecture on how DNA sequencing actually works, then explain it to someone
