We usually associate scientists with esoteric academic research rather than the nitty-gritty of business and commerce. But data scientists are different.
First of all, they don’t wear lab coats. Though more importantly, they have expertise with managing and interpreting data that’s immensely valuable to companies — which is why demand for these professionals is so high in today’s recruitment market.
What does a data scientist do?
Up until recently, firms were hamstrung by a lack of data. Marketing, finance, logistics — all these departments worked with limited information about customers, employees, processes and systems.
Over the past decade, however, commerce has transitioned from an era of data scarcity to one of abundance thanks to technologies like social media and the Internet of Things. When analyzed intelligently, this data can yield previously unobtainable insights, from market trends to customer behavior models — and can greatly improve business strategies and workflows.
In other words, data scientists make all this data talk. Specific tasks within this broad description may include:
- Guiding a company’s analytics strategy
- Finding insights in data by applying statistical models
- Using machine learning and AI to improve analytics
- Working with product owners to improve data collection strategies
Data scientists also act as advocates for data-driven decision making within their organizations. They regularly give presentations to senior leadership, and these reports can have a huge impact on the direction of the business.
How to recruit a data scientist
With data scientists, there are usually more job openings than available candidates, but we know a few tips to help you find the right person.
1. Make sure your company culture is ready
Big data has changed everything, and many companies are struggling to catch up. Some are still in a relatively early stage of the digital transformation process, which is as much about culture as it is about technology.
If you’re hiring a data scientist as part of your plan to reach digital maturity, first consider whether your company is ready for the data-driven approach. Is there an analytics infrastructure in place? Is the IT department ready to support analytics projects? Can the leadership team respond to data insights and make bold decisions accordingly?
Without widespread acceptance of a data-driven philosophy, your data scientist will struggle to make an impact — and they’ll figure this out during your recruiting process. Talk things through with the relevant teams to ensure everyone’s ready to embrace analytics.
2. Create an eye-catching job posting
To create the perfect job description, consult with your colleagues to decide what kind of data scientist you need. This means agreeing on some key details, such as:
- Education level — A master’s degree is generally the minimum, although some positions may require a Ph.D.
- Background — Do you need a mathematician with coding skills, or an IT expert with a solid grasp of statistics? Does your ideal candidate have corporate experience, or do they come from an academic background?
- IT skills — Data scientist positions always require experience with big data structures. But the role may also require programming skills, as well as a knowledge of machine learning.
- Communication skills — Data scientists must often communicate difficult concepts to nontechnical people. Good communication skills and knowledge of Microsoft PowerPoint are must-haves.
- Other soft skills — The role may require certain other attributes, such as the ability to work well in a team. Some job descriptions specify that the candidate must be a highly ethical and discreet person, as the role often involves working with very sensitive information.
What will make your ideal candidate apply for the position? Your job posting should outline why this is a great opportunity for the right person. Talk about your team structure, your goals, your organizational culture and your commitment to professional development to draw in the best candidates for your company.
3. Get the interview right
Interviewing data scientists can be tricky, since candidates may come from a range of backgrounds, from software development to pure mathematics. A good rule of thumb is to avoid asking technical questions you don’t know the answer to. If your candidate has a background in inferential statistics and you want to dig deeper, make sure there’s someone in the room who can speak with authority on the subject.
Each candidate should present a portfolio of their past work, which you can discuss during the interview. If their portfolio contains group projects, be sure to clarify exactly which elements they contributed.
4. Make an offer they can’t refuse
Salary is the most important element of any job offer package. The 2020 Robert Half Technology Salary Guide puts the midpoint starting salary for a data scientist at $125,250, though this varies by city and state. Use our Salary Calculator to get a sense of market rates in your area.
On the other hand, salary isn’t everything. Smaller employers can compete for top talent by offering attractive perks and benefits, especially those that make it easier to maintain work-life balance, such as telecommuting and flexible schedules.
Professional development opportunities can also help attract great candidates. Engaged employees are always looking for ways to improve their resumes, either by notching up new qualifications or working on interesting projects.
5. Speak to a recruitment professional
Data science is still an emerging field, and you may struggle to find suitable candidates. A specialized staffing agency like Robert Half Technology can help put together an appealing job listing and find suitable people to interview.
You may also find that it’s easier to bring in a data scientist on a project or consultancy basis. In this case, a staffing agency is practically a must. A good agency will have a roster of qualified consultants who can get started right away.
6. Waste no time
However you manage the hiring process, try to complete it as quickly as possible. If you’re keen on someone, it’s safe to assume your competitors are too. Talented candidates may be pursuing several opportunities — and are likely to accept the first attractive offer they receive. With your company’s digital future on the line, make sure that offer comes from you.