As I’m sure you’ve heard by now, Data Scientist is the “sexiest job of the 21st century”. Harvard Business Review
Even though many candidates with a strong mathematical, statistical, and computer science background are looking to move into this space, there is still a significant shortage of experienced talent. When candidates who have experience are looking for a new opportunity, they move extremely fast.
With companies like Uber, Facebook, and Amazon in the fight for the top talent, the competition is fierce! If you aren’t one of the major players you need to have a plan of action in place. You can guarantee the major players have a plan.
Your Data Science team is a crucial part of your business, and attracting the right talent can make all the difference.
HOW WILL YOU WIN THE WAR ON TALENT?
1. Have a Plan and be Realistic
Only posting on a job board isn’t enough anymore. You need to be proactive in how you go about finding your talent. Most of the candidates I work with are not actively looking. They are passive and would only make a move if the right opportunity came along. You need to have an effective and proven strategy in place before you even post the job description and begin your recruitment process.
You also need to know exactly what you are looking for in your next hire. Most data scientist job descriptions are a wishlist of unrealistic requirements and experience but are really unnecessary to perform the job you are hiring for. I highly suggest spending time writing your job description and knowing exactly the skill you need for THIS position. It’s easy to write all the buzzwords on a JD but let’s not scare off someone who would actually be perfect for the role by salivating over the purple unicorn.
2. Work with a Specialist
Working only with your HR team or a generalist recruiter, who works on all tech jobs, can be a challenge. You need to work with someone who can speak to candidates and speak their lingo. You need someone who can sell them on the opportunity at your company. When a generalist recruiter calls a Data Scientist candidate, they almost immediately get frustrated because they are already receiving 5-7 solicitations a day! The opportunity could be exactly what they would be interested in, but if it’s not communicated well, they will lose interest. Make sure you work with someone who understands the candidate’s needs and understand how to speak with a data scientist.
3. Have a Seamless Interview Process and Eliminate Inefficiencies
Time kills deals and your potential hire! The star candidate you are looking to hire more than likely has multiple interviews going on. Let’s not be naive; they are in high demand. If you want to have a seamless process, your team needs to be ready to interview, and each member needs to know the weight and role they play in the process. Multiple times, I have worked with teams who were not ready. For example, I have seen hiring managers interview candidates up to 5 rounds for a 6-month contract position. When possible, eliminate unnecessary steps without sacrificing any due diligence. The hiring process should move fast, and the candidates with skills you are looking for, move just as quick. Don’t lose your dream candidate to your competition because you didn’t act quickly with an offer.
In addition, proving feedback in a timely manner is extremely important to your recruitment process. Candidates talk, and even if they didn’t get the job, the experience they have with your company will get around.
4. Don’t forget this is a 2-Way Street
Once you know the candidate is right for the position, don’t forget to flip the switch and sell! When most of the candidates in this field are looking for their next endeavor, they want to know they are choosing a company where their skills are being utilized and pushed to higher elevations. They want to know the problems they will be solving, after all, that’s why they got into this industry. They will want reassurance the next step they are taking is the right one for their career.
I hope these tips are helpful and will help you win the war on Data Science talent!