Data Science is a Team Sport. Data Science has developed fast in the last few years due to a range of technological advancements and the ubiquitous nature of structured and unstructured data. Now, Data Science has impacted every industry. Demand for specialized knowledge has increased. As a consequence individuals can’t master every aspect of Data Science. It is now more important than ever to gather the required level of knowledge through teamwork.
A variety of roles and skills are now required to ensure the success (and not the failure) of a Data Science project. The main roles include:
Some roles only require one type of skill set. This may be analytical, technology, or business skills, for example. Other roles rely on the intersection of two skill sets. These roles include data architects, data scientists, and analytical translators. All of these roles play an important role, in connecting two different worlds.
According to McKinsey, the analytical translator is the new must-have role. Translators typically have a very versatile profile with skills: business and domain knowledge, and project management as well as strong acumen in quantitative analytics and structured problem-solving. Their unique skill set can help businesses increase the return on investment from their analytics initiatives. Translators are instrumental in identifying the right opportunities to pursue, helping to ensure that all team members work in harmony.
It is important to bridge the technical expertise of your data engineers and data scientists. Most importantly, with the operational expertise of marketing, supply chain, manufacturing, risk, and other frontline managers.
