“What’s in a name? That which we call a rose by any other word would smell as sweet.” (Shakespeare, 2.2. 43-45)

Just like a rose retains its essence regardless of its label, the true value of computational talent in biotech lies far beyond the job title. Are you a biotech leader navigating the complex waters of hiring bioinformatics, software, data science, AI/ML talent, often wondering what truly differentiates a computational biologist from a bioinformatics scientist? You’re not alone. I’ve recently had several conversations with biotech leaders without a deep technical background in these areas and who understandably struggle to distinguish between the rapidly evolving job titles and roles. This complexity has grown organically along with the big data era of biology. New roles emerge constantly, and the definitions can both overlap but also vary significantly between organizations and even between different teams within a large organization. Each title might imply a specific blend of skills and knowledge but the exact mix is rarely obvious from the title alone.

This ambiguity poses significant challenges for hiring managers, project leads, and even investors. Without a clear understanding of what each role entails, organizations often mis-hire and then do not have the right blend of skills. You might hire a brilliant bioinformatics scientist who is statistically minded and excels at algorithm development, only to find that your project actually needed someone with stronger software engineering skills who could deploy that algorithm as a robust, user-friendly application for non-experts.

To navigate this complex landscape, non-specialists can start by focusing on the end state. What are the outcomes they want to achieve and are there any relevant constraints such as from the operational environment? This can then be translated by a domain expert into a detailed digital science and technology roadmap. This planning enables us to determine the precise blend of skills required, regardless of what the job descriptions are ultimately called. Sometimes, what you really need is not just a “bioinformatician” but someone with expertise in genomics, software engineering, diagnostic applications and regulated environments”. The key is to look beyond the name and delve into the actual skills, mindset, capabilities and experience.

If your organization is grappling with these challenges, consider how expert advisory services can help you to clarify your needs, build a technology roadmap aligned with your objectives and identify the right skills and capabilities to meet your unique objectives both now and in the future.

Please connect with me at [email protected] to discuss how I could help.