(US and Canada) Sharath Gokula, Director of Data Science & Analytics at Walmart e-commerce speaks with Tristan Spaulding, Head of Product, Acceldata, about data science as a career, important data skill sets, transitions in the data field, organizational role and culture that drives data excellence, and tackling technical challenges while operating both digitally and on-prem.

Gokula starts the discussion by stating that data science has an engineering and mathematical aspect to it. Given the vastness of data science, data career enthusiasts must be aware of what stimulates them. It could be in the analytics aspect enabling better decision-making involving humans, or could be in the data engineering aspect curating the data flow into the data stream. Interest could also lie with machine learning where systems are built and integrated into engineering. He also stresses thorough reading of available resources and learning programming skills before shifting to data science.

Gokula further mentions the garbage in garbage out aspect of data science and thus it is critical to get the data right. Speaking of skill sets, he asserts that some of the skills are acquired through work, and some skills related to the engineering aspect need to be learned. An awareness of the data stack is required, but one doesn’t need to be an expert in everything, he says.

Highlighting the role transitions, he states that there are engineering-centered roles within data science, like data engineering which has more engineering than analytical functions. Likewise, a Machine learning engineer is somewhat of a statistician and engineer, and analytical engineers have the business nerve.

The marketing factor also aids in transition, says Gokula. And this intersection is evident as people in the analytics sector enhance their skills and transit into data scientist roles. The transition also applies at an organizational level, where after taking the data course, general skills will only be of limited help. For enhanced optimization, data specialists are required, he states.

Gokula then affirms that his role at Walmart is to lead product candidates and he focuses on on-site experimentation, outlier detection, and within respective teams. Walmart treats data as a key differentiator, he adds. Considering the evolving e-commerce businesses, the importance given to customers’ needs leads to a successful business, which is impossible without data.

In conclusion, Gokula states that to tackle the technical and competitive challenges, one needs to be informed about the data market and make better decisions. Secondly, understanding customers’ need for change and incorporating cloud technology to address their needs is a complete necessity.