Top 10 Strategies to Attract and Retain Data Scientists in 2020

Top 10 Strategies to Attract and Retain Data Scientists in 2020

by August 6, 2020

Data Science

Data Science Professionals are in great demand, employers have to be on top of their game to keep this valuable resource safe from competitor poaching!

Let’s accept the fact that data scientists are in short supply, difficult to find and tougher to retain!

It could be a vexing challenge to retain a data science professional who is spending on an average of one to two hours per week looking for new jobs and interacting with potential employers. They are often millennials who are passionate about technology, learning to show their knowledge and calibre to the world.  So how does an enterprise ensure that they have enterprise loyalty and don’t add to the attrition rates?

Here are the Top 10 Strategies that help Enterprises to attract and retain data science talent-


1. Help Data Scientists Invent

The new joiners are people who want to learn something new, they get bored easily if they are asked to do the same route-based work every day. Data scientists are scarce talents and if they are asked to spend their time performing repetitive tasks like data acquisition, data management, they may feel underutilized. It’s a good tip to let them learn and invent new ways with forward-looking projects to explore how the enterprise can benefit from big data.


2. Thinking Out of the Data Box

Data scientists are natural learners who have a 360-degree view, let your data scientists think and act outside the box. This will prove to be a great learning medium and keep them motivated to work


3. Let them Work Cross-Departments

Let data scientists collaborate with professionals from operations management, digital marketing, or customer relationship management teams. Introducing multiple roles and avenues of work for data scientists makes sure that teamwork is on track and employee stickiness is maintained.


4. Adopting a broader Business Mindset

Enterprises must sharpen the business acumen of data scientists to contribute and initiate analyses and experiments. Consider data scientists to build their own data stories and communicate them to the C-suite on the C-suite’s terms


5. Let data scientists collaborate with the C-Suite

Without C-Suite communication and direction, data scientists may end up working on the wrong problems. Data Scientists must be engaged in two-way communication with the C-Suite to help define the business problem, devise a solution approach and weigh its business outcomes.


6. Offer work flexibility

Data Scientists are creative young minds who can work from anywhere. Much to the impact of Covid-19, remote work has become the new norm. While remote working, keep connected with them and develop a strong corporate culture to make them feel their importance to the enterprise.


7. Recognize Achievements

Sometimes, good words of motivation and appreciation is all it takes. Recognize your data scientists, for their work. Let them know how vital is their contribution to the business.


8. Offer Tech Support

Build a work-friendly environment that data scientists will love to work in. Ensure the enterprise has the latest software tools. Check if your IT has data science tools that are fast enough? Slow data clusters wipe away the motivation and enthusiasm of data scientists and saps both their motivation and creativity.


9. Offer On the Job Training

Data Science is a dynamic disciple, and new changes are coming each day. Enterprises must make sure their data science staff is well trained and in touch with the latest data science tools and advancements. Offering on-the-job training will not only ensure that data science professionals are updated it will also make them feel wanted by the enterprise.


10. Build Ownership

Let the data scientists spend time more with businesses and product units to better understand the real business problems at hand. This will make them feel more valued subsequently strengthen their analyses and understanding of your business.