Data Science

Strategies that help companies attract and retain data science talent

10 strategies that help companies attract and retain data science talent

In a digital world companies need to utilize technology, knowledge, computational power and access to data, whilst recognizing that insights are the new business currency.

Companies attempt to empower their workforce, to make them citizen data scientists only to fail partly because the approach has been technology focused. From data warehousing to big data and most of today's AI solutions; all of these are mainly built for Data Analysts, Data Scientists IT Wizards. Demand for Data scientists (and various associated roles) is high, availability in short supply, expensive, difficult to find and tougher to retain. Insufficient expertise creates bottle necks that slows down progress or completely disadvantages companies who are unable to compete for the talent and attain the necessary skillsets. The playing field is tilted in favor of large enterprises, and even they have resourcing challenges. How can an organization attract and retain data science talent, and less resourced companies level the playing field?

1. Enable Data Scientists to invent and explore

Spending their time performing repetitive tasks like data acquisition, or data management is unlikely to stimulate a data scientist who will most likely feel  underutilized. Data scientists are natural learners who have a 360-degree view. Provide opportunities to learn and invent new ways with forward-looking projects to explore how the organization can benefit from data science. This will prove to be a great learning medium and keep them motivated to work.

2. Let them work across departments

Let data scientists collaborate with professionals across all business disciplines and teams. Introducing multiple roles and avenues of work for data scientists makes sure that teamwork, collaboration and solutions are leverages throughout the company, work stays on-track and employee motivation and stickiness is maintained.

3. Adopt a business mindset

To be effective, define challenges and truly contribute through initial analysis and experimentation data scientists need to have a business mindset. Facilitate data scientists enabling them to build their own data narratives and communicate the use cases to the leadership in their terms.

Encourage data scientists to collaborate with the leadership team

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 business problems, devise a solution approach and weigh business outcomes. What data science expertise do you have on your leadership team?  Would having access to a trusted data scientist advisor help your leadership team?

4. Offer work flexibility

Data Scientists are creative focused, purposeful and can work from anywhere. Allow remote working, keep connected and develop a strong corporate culture to make them aware of their importance to the company.

5. Recognize Achievements

No different for any employee. Understand what motivates each person. Sometimes words of appreciation go a long way. Recognize your data scientists, for their work and ensure they know how critical their contribution is to the business.

6. Provide the right environment and support

Ideally provide an integrated development environment (IDE)- A work-friendly environment that data scientists love to work, collaborate and share in. Deliver the ability to build, deploy and iterate fast and efficiently, so that decision makers feedback can be quickly incorporated to update the solution(s), and stakeholders have the tailored decision-making support they need.

7. Deliver on-the job training

Data Science is a dynamic disciple, constant changing. Companies must ensure their data science staff has access to quality training, certifications and are in touch with the latest data science tools and advancements. Providing on-the-job training helps ensure that data science professionals are updated and make them feel wanted by the company.

8. Facilitate and encourage an ownership approach

Enable data scientist to spend quality time with businesses and product units to better understand the real business problems at hand. Business perspective and context lifts the potential a data scientist can bring to bear and application of their skills to help solve unseen challenges. Make them feel more valued while concurrently strengthening their analysis and understanding of the business.

9. Data Science as a Service - DSaaS

The lines of businesses within organizations are pushing hard on rapidly using services and extracting value from data and the pace is accelerating.

DSaaS helps democratize data science by providing custom access to expert resources to support all companies throughout their data science journey providing various solutions and flexible engagement models to optimize resources and outcomes

Our mission, culture, opportunities for diverse project engagements across broad industries and entire value chain is fundamental to attracting and retaining the expertise necessary to deliver clients end to end data science.  

A range of flexible engagement models to optimize resources and outcomes  

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