In a nutshell:
- Hiring your first data scientist can be daunting, but it's crucial for taking your business to the next level with machine learning and AI projects.
- Look for candidates with a solid technical background in statistics and machine learning and relevant business experience.
- Consider leveraging existing talent within your organization before recruiting externally. Upskilling current employees may be a more pragmatic approach.
How to Hire Your First Data Scientist
So you've decided that your organization is ready to add data science capabilities. You want to make the most of the data you've collected, and you know there's more you can do beyond descriptive analytics and dashboards. It's time to launch machine learning and AI projects that will take your business to the next level.
But hiring your first data scientist can be daunting. You want to make sure you do it right.
And, of course, there's the cost: The median salary for a data scientist in the United States, as reported by the U.S. Bureau of Labor Statistics (BLS) in 2023, is $108,020 annually. That doesn't include other components of their compensation.
How can you ensure the data scientist you hire is a good fit? Here's what to focus on.
Ensure Relevant Background
First, confirm the data scientist has the proper foundations. Do they have statistical and machine learning expertise? Can they build the types of predictive models you need? Technical skills are important to evaluate.
Seek Relevant Business Experience
However, technical chops aren't everything. Just as critical is whether a candidate has applicable real-world experience. Have they worked on similar use cases before at comparable companies? Business context matters when data scientists tackle AI use cases.
Leverage Existing Capabilities
But here's a tip you might not expect: Before hiring, audit your current talent. Can your BI developers or analysts do the work? With user-friendly tools like Pecan, they can become AI data analysts, building sophisticated models without needing advanced data science degrees or in-depth AI knowledge.
Upskilling and promoting from within may be more pragmatic than recruiting externally, while also conserving resources.
Ready to Get Started?
Hiring a data scientist is a big commitment. But you may already have the skills in-house. Schedule a chat with our product specialists to learn more about how Pecan can help your team achieve its AI goals faster than ever.
Zohar Bronfman is the co-founder and CEO of Pecan AI, working at the intersection of machine learning, causality, and real-world decision-making. He holds two PhDs—one in computational neuroscience and one in the philosophy of science—bringing an unusually rigorous lens to applied AI. Zohar focuses on turning predictive models into systems that reliably change outcomes inside complex organizations. He is a frequent voice on the future of AI and decision intelligence, with appearances in top-tier tech and business media and on leading industry podcasts. His work bridges deep theory and execution, aiming to make artificial intelligence both more accessible and more consequential.
