Dear Advisor: How to work with a data scientist?

May 2022

You keep hearing that “data is the new oil” and are considering hiring a Data Scientist to help you. But do you need one? How do you evaluate their skills? What are some tips to make sure the collaboration is off to a good start? 

I’ve been in the Data space for over 10 years, managing, hiring and mentoring Data professionals – and collaborating with executives of companies of all shapes, sizes and industries on data-driven initiatives. Here’s my advice to help you answer these questions

Step 1: Evaluate – do you need a DS?

As you may know, hiring and retaining knowledgeable people in tech is hard, especially now. Let’s make sure you actually do need to hire one – and if you do, whether that should/not be a data scientist.

If you've answered ‘no’ to any of the questions above, at this point-in-time, hiring a Data Scientist is not the right solution to solving your pain point. 

Question: OK, I won’t hire a Data Scientist just yet. Whom would you recommend?

Step 2: Recruit – how do you hire a DS?

It sounds like a Data Scientist may be the right hire at this point. Great! Here’s advice to guide your hiring process, including tailoring the job description to the skills that will help you solve your processing business challenge.

Question: OK, but what if I’m not technical enough to evaluate their skills – and also don’t have anyone on my team to help. What do you recommend?

That’s a great question! I recommend leaning on your technical advisor(s), board member(s), fractional data executives (like me) – or someone with a Data background you trust in your network, to help you interview candidates.

Step 3: Collaborate – how to successfully work together?

You’re now ahead of the curve. You have an actionable business question you need help trying to answer. Go ahead and share that context with your new hire; here’s a template I use– and includes the recommendation of discussing checkpoints along the way.

I also recommend sharing and finding out more about how each of you collaborates best. I share advice with strategies and talking points here, on how to stay on the same page throughout the collaboration.

At the end of the collaboration, I highly recommend a post-mortem, to evaluate:

Step 4: Maintain – any advice on long-term data science strategy? 

Question: You mentioned that data and data science are expensive investments. If data is core to my business, will there ever come a time when I can stop listening to data?

That’s a great question! In my (potentially biased) opinion, the answer is “most likely not” for these 3 reasons:

Parting Advice, Caveats, Challenges and Pitfalls

I’ll admit, this 4-step process sounds deceptively simple. What can go wrong?

Challenges notwithstanding, you’ll learn something new – whether that’s about your customers, your product, or business – or how to better collaborate on the next project.

Are you getting enough applicants? Do you need to improve your job description? Please schedule this flat-fee session.

Good luck! If you’d like more support at any step of this process, please reach out. I’d like to help you understand and solve your customers’ pain points and support your team.

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