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How Data Scientists Can Thrive in Consulting

Pratik Agrawal, Partner at Kearney, joins us to discuss how data teams can scale value in consulting environments. 

Feb 2023

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Pratik Agrawal

Pratik Agrawal is a Partner at Kearney Analytics, leading the automotive and industrial transportation sector. As a software engineer and data scientist with over a decade of experience in the consulting world at companies like Boston Consulting Group and IRI, Pratik has a deep understanding of how to navigate the industry and how data science can be leveraged in it, as well as expertise in digital transformation projects and strategy.

Photo of Richie Cotton
Richie Cotton

Richie helps organizations get from a vague sense of "hey we ought to get better at using data" to having realistic plans to become successful data-driven organizations. He's been a data scientist since before it was called data science, and has written several books and created many DataCamp courses on the subject.

Key takeaways


Curiosity, communication, and a passion for problem-solving are all important skills to cultivate for any data professionals considering a career in consulting.


Data-driven decision making has become much more pervasive throughout all of consulting, increasing the need for every role to increase their data literacy.


Domain expertise is something that grows over time, but in consulting, you close that gap by learning through exposure to different industries and by working side-by-side with the clients who have the domain expertise needed to complete a project. 

Key quotes

One thing I've found that has changed over the last several years in consulting is that we've become much more accustomed to working with data in everything we do and across every role. So it's not just the analytics practices or the AI practitioners, but it's the broader sort of consulting landscape. That’s because we’ve begun to think about where we are driving decisions from, which has led the industry toward data-driven decision-making to the point that it’s basically baked into almost all parts of consulting.  

The time pressure  in consulting is much different than in other organizations. There's always a, a timeline that one is working against, but working with data in a consulting firm is usually dependent on whether we actually have the data and how long it takes for us to get the data so we can begin working on an initial hypothesis, impacting the timeline significantly. start working on a, at least an initial hypothesis. A lot of time also gets spent on data cleaning and building sort of a single source of truth that the team can utilize to get the job done right.


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