Bolster Your In-House Talent to Meet the Growing Shortage of Data Scientists


Data have become the golden key that unlocks the insights you need to boost customer loyalty, optimize inventory, enhance production, and discover new markets, to name a few. The challenge for many organizations is finding someone who has the skills to turn that key. Extracting business value from data demands a unique combination of skills.

Job postings for data scientists have risen by 75 percentOpens a new window over the last three years, indicating that businesses are having a difficult time sourcing people who have the education and talent to fill the role.

One overlooked source of data scientist talent could be found within the organization—and not just the IT department, opening up the pool of resources to a broader range of candidates. “When you are looking for people who can help you unleash data to drive profits, your best candidates may not necessarily be limited to IT,” says Tim Newcome, president of Ambassador Software WorksOpens a new window . “Your best candidates are those who do not necessarily know what the answer is, but instead, know how to ask the question.”

One of the key skills of data scientists is to have a thorough understanding of your business—a component that will be lacking from any outside data scientists, no matter how comprehensively they are trained. Sometimes, training an inside person to think like a data scientist may make more sense and could be more efficient. When looking for candidates, recognize what skilled data scientists must be able to:

  • Understand the business problem so that they can build a model that is critical to solving the problem.
  • Be comfortable working with statistics within the methods to ensure preparation of the data.
  • Select the appropriate algorithm.
  • Be curious and have enough business sense to understand which data are likely to be relevant.
  • Communicate with business stakeholders, such as how an algorithm arrived at a specific prediction.

Opening the door wider to find people to source talent to fill your data-scientist roles could include drawing people from the marketing and the executive support team. “Marketing people are accustomed to working with ambiguity and have the ability to draw inferences from the data,” adds Newcome. “They understand probability and the importance of segmentation.”

Here’s how to make an in-house data scientist recruiting program work for your organization:

Spread the Word

Make an announcement that you are looking for people who are interested in making a career change. Show employees what is possible, and be open to assisting employees who have the desire but may have underutilized skills. Take the time to listen to their career goals while reviewing their history, education, training, and experience. Be open to the possibility of adding people with different strengths who could make an excellent addition to your team.

Offer Paid Employee Training

In addition to learning on the job, offer paid educational programs. Don’t be afraid to explore hackathons as an excellent way for those who are willing to learn to get hands-on experience in real-life business scenarios and develop problem-solving skills.

Create Customized Training Programs

Tailor the program to match the employee. Specialists from marketing may need to learn to code, for example. Others may have the coding skills but require specific training in data analytics or business training.

Provide Opportunities to Work in Data Scientist Roles

Create an in-house training path that includes a series of internal roles. These positions could consist of the back-end database pipeline roles, including data visualization, data analytics, and data hygiene roles. These positions allow your growing team to build their core data skill sets while providing opportunities for them to work and learn from experienced data scientists.

Focusing on building a data scientist team, rather than finding the right person with the ideal skill set, could prove to be more beneficial over the long term. Finding someone with the right mix of analytical and intuitive skills may not always be possible. A team approach could be a much more insightful and valuable strategy.