In this blog, we will learn in detail about the recruiting process and assessments needed to hire a data scientist. Data scientists work with complex data to bring out meaningful, actionable insights. They help businesses predict consumer behaviour which can be used to increase the overall revenue. Data scientists have a tall order in terms of skills. They not only need to have skills in statistics and math, but also in big data, machine learning and more. It is also imperative that they have domain knowledge of the business you’re hiring for. But it can be quite challenging to hire the right fits for this role as they are in high demand in the market. Also they require a unique set of skills, which many candidates may not have. Hire the best data scientist with this basic recruitment process – identify & screen, assess, interview and onboard.
What do data scientists do?
Data scientist hiring has been on the rise for a while now. As per a research by Statista, the percentage of organisations that hire data scientists has increased from 30% in 2020 to almost 60% in 2021. Businesses are increasingly looking to lighten their data analytics with the help of data scientists. Data scientists analyze structured or unstructured data to find meaningful insights. They look for patterns in data and use their comprehensive industry knowledge to come up with answers to complex problems and helpful business solutions. They are part mathematicians and part computer scientists, and many of them started their career as statisticians or data analysts. But as big data began to evolve, this role evolved too.
How do data scientists help businesses?
Data scientists help businesses handle large amounts of data and solve complex problems. They lay a solid data foundation to perform robust analytics. They also convert massive data streams into solid, actionable insights. In businesses, data scientists typically work in large teams to mine data for information. This information can then be used to predict consumer behaviour and identify new revenue opportunities.
Data scientists demystify big data to unlock its power. They are trained to identify unusual and so with their big data methodologies, they can predict fraud and help mitigate it by creating alerts. They can also help businesses deliver the right products at the right time. With their deep understanding of the consumers, they can help create the best possible experiences for them.
What skills to look for in data scientists?
- Math & Statistics: A working knowledge of calculus, probability distribution, algebra, and more is necessary.
- Python programming: Python programming is a necessary skill as it can be used for plenty of functions like data mining, website construction and running embedded systems.
- R programming: This can help implement machine learning algorithms fast and gives a variety of statistical techniques.
- Hadoop platform: This bundle of open-source software utilities can help process large data sets
- SQL databases: SQL can help read and retrieve data from a database.
- ML & AI: ML helps to analyse large blocks of data using algorithms.
- Data visualization: Data scientists should be able to visualise data with the help of tools like ggplot, d3.js, and Tableau.
- Business strategy: Business acumen is a very important skill to have for them to understand business problems and figure out the corresponding solution.
- Communication, critical thinking & problem-solving: Data scientists are required to analyse complex business problems and come up with creative solutions.
Challenges to hiring data scientists
Chances are, the candidate you have offered the job to, has multiple other offers in their kitty. Your employer branding must be strong enough to make you the preferred employer. You can also make sure to keep them engaged and build a personal rapport with them. This will help in building a good relationship with them and hopefully make them choose your organisation over others.
Another challenge may be skill gaps in your selected candidates. By the end of the interview process, you would have most likely been able to check their skills and lack thereof. But this challenge can be overcome by upskilling your candidates in the required technologies. You can either upskill internally or outsource it.
Steps to hiring data scientists