With U.S. data science jobs projected to grow 35% over the next decade, a recruiter and talent strategy director discuss the qualifications, technical skills and mindset needed to land these coveted positions.
Those hoping to land data science roles at biopharma companies will likely appreciate the latest findings from the U.S. Bureau of Labor Statistics. The agency predicts the U.S. data science occupation will grow 35% from 2025 to 2035, resulting in 95,400 new jobs.
Looking at biopharma specifically, the over 500 data science positions posted on the BioSpace website reflect the increasing importance of people who can apply data insights throughout a drug’s life cycle, from discovery to commercialization. As to which roles are most in demand these days, there are three, according to Darren Nelson, founder and CEO of Recruits Lab, a recruiting firm that specializes in artificial intelligence, life sciences and technology. Those roles, he told BioSpace, are computational biologists for genomic data, artificial intelligence and machine learning discovery scientists for predictive drug modeling and translational data scientists for clinical trial and real-world evidence analysis.
For a look at what employers are looking for when filling data science roles, BioSpace spoke to Nelson and Gio Amari, director of talent strategy at Beeline Medicines.
Who’s applying vs. who employers want
Two main groups of people apply to data science roles, according to Nelson: life sciences professionals who have Ph.D.s and picked up machine learning to analyze their own research and traditional tech talent like computer scientists or software engineers looking to move into healthcare. He sees slightly more of the first group of people pursuing open biopharma positions. Regarding the latter group, Nelson noted that some people can move easily between industries. For example, he said, software engineers are pretty industry agnostic and can transition from a fintech business to a life sciences company.
When it comes to which type of people biopharma employers like to hire for data science roles, Nelson noted that there is a fairly even split between the two main groups. Some, he said, prefer life sciences professionals who have Ph.D.s., but others like computer scientists or software engineers from other industries because of their experience “getting their hands dirty and getting the work done.”
Company size can influence preferences, according to Nelson. Many startups, especially venture-backed businesses, he said, want someone with a Ph.D. from a top-tier university like Carnegie Mellon University, California Institute of Technology or Stanford. They also want candidates with real-world experience at a venture-backed startup or a well-known larger company so no ramp-up time for learning is required, he noted.
“These startups, they have their timelines, and they’re trying to get to that finish line as fast as possible,” Nelson said. “So, having that experience where they can seamlessly jump on board is pretty important there.”
Technical, soft skills candidates must have
There are several technical and soft skills data sciences candidates need to possess, according to Nelson. For technical skills, he noted that experience with programming languages Python and R is nonnegotiable, alongside specialized tools like Biopython, RD Kit and PyTorch. He also highlighted standard data pipeline skills including SQL (structured query language), AWS (Amazon Web Services) and Docker.
In addition, Nelson said his firm is seeing a lot of artificial intelligence being introduced into high-level scientist roles, so it’s important that candidates use that technology to their advantage so they don’t get left behind.
As to must-have soft skills, Nelson noted there’s a need for people whose cross-functional communication experience allows them to translate complex results into plain, actionable language for biologists, chemists and executives. Sometimes people in highly technical roles can have difficulty explaining their findings, he noted.
“They can’t translate it into digestible ways that people without technical knowledge can understand it, essentially,” Nelson said.
What makes candidates stand out
Some factors make data science candidates stand out more than others to employers, according to Nelson. One he noted is understanding biological realities rather than treating biology like a simple math problem. Another is showing a portfolio that solves a real drug development bottleneck.
“It’s all about solving the problem, right?” Nelson said, adding that companies appreciate it when candidates can not only dissect but also fix development issues.
How candidates present themselves during interviews also matters, according to Nelson. Sometimes, he said, those who look great on paper don’t do well in the interview process. On the flip side, he added, his firm has seen people who don’t come from the best school or have the most impressive background interview well. They research the company and clearly delineate how they’re going to solve the employer’s problem, and they get the job, he said.
“So, it’s not all about what’s on paper,” Nelson noted.
Beeline’s approach to data science roles
One employer looking to fill a data science role now is Beeline Medicines, a Stamford, Connecticut–based biotech focused on developing and delivering precision therapies for the treatment of autoimmune and inflammatory diseases. The company is hiring for a senior director, biostatistics, to join its research and development team. Within that team, Beeline has five quantitative employees who sit within biometrics—biostatistics, statistical programming and clinical data management—and in research-side computational and translational roles working on target biology and biomarker strategy.
For the senior director of biostatistics role, Beeline is looking for someone with three nonnegotiable skills, according to Amari. Candidates should have methodological depth, broad submission experience and fluency in data standards and analytical tools such as SAS, R and CDISC, he told BioSpace in an emailed response. The role also requires someone with a Ph.D. and extensive experience in drug development that reflects the scope of responsibility and accountability that corresponds with the opportunity, Amari noted.
Beyond the technical skills, how candidates work will decide who Beeline hires, according to Amari.
“We’re looking to build our team with individuals who are versatile, adaptive, and agile—those who can balance big picture thinking with tactical execution,” he said. “Candidates who become Beeliners care hard, and innovate with rigor, quality, and urgency.”
As to leaders specifically, Amari noted that those who thrive at the company leave their ego at the door. They share the credit, never hesitate to help and always step in where they are needed, he said.
“What ultimately sets candidates apart is that they bring both the what and the how: the outcomes they’ve delivered, and the genuine care for patients and colleagues that shapes the way they get there,” Amari said.
