As market values increase for computational biology and data science, biopharma companies are looking to hire R&D professionals in those areas. A biotech talent acquisition expert shares his insights on these in-demand roles.
Research and development jobs are a priority for biopharmas, according to a recent BioSpace workforce planning survey where 60% of respondents said they anticipate hiring in R&D in 2025. Some also called out the oncology space as an area of high demand—but which oncology R&D roles are companies looking to fill? Computational biology and data science are hot areas for hiring, according to an industry talent acquisition executive.
There’s a demand for more computationally focused behind-the-computer type roles, said Conor Sullivan, associate director and head of talent acquisition at Harbinger Health, a Cambridge, Massachusetts–based biotech that develops technologies for cancer screening and detection. The company uses artificial intelligence to help identify cancer before it’s visible or symptomatic with the goal of developing low-cost, multicancer blood tests.
In the recent BioSpace survey, respondents supported Sullivan’s observation about behind-the-computer roles, noting that structured query language, Python and AI are among the R&D skills they expect to be in high demand in 2025.
Sullivan told BioSpace that Harbinger has most recently focused on computational biology and data science roles that border on machine learning. He said the jobs involve having a good, broad base of knowledge that allows employees to leverage more off-the-shelf tooling to expand their ability to analyze data.
Multiple companies have computational biology and data science roles in the oncology space posted on the BioSpace website. Examples of recent computational biology positions include senior principal scientist, computational biology at Amgen and vice president, translational data science/computational biology at Recursion. Examples of recent data science roles include principal data scientist at AbbVie and vice president, global business digital insights and analytics-oncology at Takeda.
Computational Biology, Data Science Markets Projected to Grow
The importance of computational biology and data science is reflected in their growing market values. The global computational biology market is estimated to increase from $6.6 billion in 2023 to over $20.5 billion by 2030, according to Coherent Market Insights. The global market intelligence and consulting organization attributes that growth to biopharma companies’ growing demand for predictive modeling and noted that pharmas use computational biology techniques for drug discovery and development.
The global data science platform market is estimated to increase from $11 billion in 2024 to $45.9 billion in 2031, according to Coherent. The organization attributes that growth to widespread adoption of data-driven decision making across various industries. Coherent also noted that increasing focus on generating insights from structured and unstructured data to gain a competitive advantage can boost demand for data science platforms.
All of this is not to say that lab-based R&D roles in oncology are not in demand. For example, Sullivan noted that at Harbinger, there’s a significant need for biopharma professionals who know the cell biology behind the genesis of cancer so they understand what’s happening at the earliest formations of the disease. He said the company’s lab-based employees usually have a molecular biology background.
Key Hard and Soft Skills: From Sequencing to Communication
For data science and computational biology roles, Sullivan said Harbinger looks for biopharma professionals who understand the epigenetic and methylation changes that occur in genomic data where cancer is present. The company also wants people who understand how to translate those changes into biomarkers that enable them to not only understand different types of cancer but also track how they progress. Sullivan said sequencing is a big focus in terms of skill sets.
Companies that have posted computational biology jobs on BioSpace, such as Amgen and Recursion, have noted interest in technical skills such as expertise in bioinformatics; experience with programming languages such as R and Python; and knowledge of platforms and readouts used to assess clinical biomarkers, including flow cytometry, immunoassays and single-cell assays.
Biopharmas that have listed data science positions on BioSpace, such as AbbVie and Amgen, have requested qualifications including demonstrated analytical skills; experience in physicochemical or analytical characterization of biological molecules; and experience developing and implementing patient stratification/precision medicine solutions in clinical development, leveraging multi-omics and clinical data.
Soft skills are also sought after. For example, a recent Amgen job posting for a computational biology role listed strong written and oral communication skills, self-motivation, independence and leadership as preferred qualifications. Sullivan noted that communication, organization and collaboration are important to Harbinger and especially to smaller companies.
“It isn’t necessarily we look for the best oncologist in the world, and they need to have these communication skills,” he said, adding that striking a balance between hard and soft skills is helpful. “I would say in any small company—100 or less, or even 200 or less—being comfortable, confident and wanting to have that collaboration and communication is really beneficial to not only your career but the overall company and team that you’re working with.”
Advice for Early-Stage Job Candidates
When it comes to advice for job candidates applying for data science and computational biology roles, Sullivan focused on grad school students looking to develop skills that will be applicable for industry. He recommended learning Python, for example. Sullivan also advised that grad students work with computational biologists at school to understand how to analyze and leverage data to accelerate projects.
“In thinking that way, what you’re really doing is you’re being proactive about what other technologies exist, and how can I utilize those things to further my goal, my project, my scientific team,” Sullivan said.
He added, “If you’re taking that proactive approach, then thinking about what the emergent technologies are, looking at what industry is focusing on in some of those job descriptions and trying to partner with and reach out to groups or individuals that have those skill sets will really set you apart.”
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