How Healthcare Can Attract Top Data Scientists

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I work as a data scientist in the healthcare payment integrity space. I can attest that seasoned quantitative leaders are highly sought after — I get outreach from recruiters weekly trying to entice me to other jobs.

To me, data scientists in healthcare are especially valuable. But here’s the problem. Demand for data scientists is soaring but there aren’t enough of us to hire. According to theLinkedIn 2020 Emerging Jobs Report, the data science field is seeing “continued growth on a tremendous scale.” It’s the №3 emerging job with 37% annual growth. And it’s projected to grow 15% between 2019 and 2029 — much faster than the average for all occupations, according to the U.S. Bureau of Labor Statistics.

Here are four ways to attract and retain top-notch data scientists in healthcare:

Innovation holds appeal. The unprecedented adoption of AI in healthcare presents an enormous opportunity for data scientists. Like me, many data science candidates are attracted to companies born with AI in their DNA. While emerging companies can be attractive to data scientists, legacy organizations should showcase their roadmaps to revitalization — through data and analytics projects to appeal to data scientists. Typically, data science candidates seek big challenges that deliver impactful outcomes. Both older and newer providers of healthcare solutions, including those that address payment integrity, offer ample opportunities for meaningful data analytics work.

Experimentation. Build a playground for experimentation Create an environment with flexibility and room for experimentation where data scientists can exercise their creative freedom. And show us we can grow. Data scientists don’t want to be held back. Security restrictions are inherent in the healthcare industry but get us excited about the critical work we can do and the impact we’ll have. Payment technology is complex and the chance to attack involved and intricate challenges is a draw for data scientists looking for impact-driven projects. Connect our work to a clear professional development pathway, with the ability to work with teams of different strengths and sizes.

Mentorship. When you create meaningful programs to encourage the right talent to stay, in the form of mentorship or other initiatives, they will naturally be more engaged and embrace the culture. Across industries, helping junior team members weave through the demands and pressures of the role helps on multiple levels. Developing soft skills like leadership, communication, ideation, and collaboration helps team members to visualize their full potential. In healthcare, and specifically payment integrity, the data dive is deep, the integration process is time-consuming but the outcomes are rewarding. Help us to see the impact of our work.

Collaboration. In healthcare, the challenge is finding data scientists who understand the complexities of data involving multifaceted relationships between stakeholders and organizations. Ideal candidates have strong business acumen, deep expertise in statistics, machine learning and software development, domain knowledge, leadership, and communication skills to be most successful. This candidate is not easily found. One solution is to move toward collaborative teams that support each other, instead of searching for the elusive unicorn that possesses all these skills.

Competition is fierce. Big tech giants like Google, Amazon, and Facebook are pouring enormous resources into finding top-notch talent, further shrinking the pool we must choose from. By focusing on data scientists’ desire to learn from others, experiment with advanced tools and technologies, and contribute measurably to a better healthcare ecosystem, you’re more likely to keep working with you for years to come.

Saurav Subedi is the Director of Data Science at Codoxo, a provider of healthcare AI solutions.