In the 12th episode of Datacast, I had a conversation with Jim Leach, a data scientist at the consulting firm KPMG. Give a listen to learn about challenges in applying data science in consulting, his experience getting a Master degree in Business Analytics at Imperial College of London, the benefits of teaching to others, and many more.
Jim Leach is a data scientist, originally from the North of England, but now based in Atlanta, Georgia. After studying chemistry at university, Jim joined the consulting firm KPMG and began his career as a data analyst. He later returned to university, taking a sabbatical to study for a Master in Business Analytics at Imperial College, London. In his work, he is a passionate R user and developer and enjoys thinking about data visualization and how to communicate effectively using data. In his free time, he enjoys board games, music, cooking, and being outdoors.
Show Notes
(2:16) Jim recalled his experience getting a Bachelor Degree in Chemistry at the University College of London.
(4:01) Jim talked about the analytical skills that he got out from his Chemistry degree.
(5:09) Jim gave a brief background overview of his employer KPMG, one of the big 4 consulting firms.
(6:56) Jim shared the major challenges of applying scientific rigor to identify and quantify business opportunities using data.
(9:42) Jim reflected on his professional growth working after 3 years working as a data analyst at KPMG.
(12:23) Jim explained his motivation behind his decision to pursue a Masters in Business Analytics at Imperial College of London.
(16:27) Jim recalled the most useful courses he took during his Master degree (Graph Analysis on the technical side and Marketing on the business side).
(18:40) Jim talked about the importance of learning econometrics for a data scientist.
(21:22) Jim talked about the benefit of teaching materials to other people that contribute significantly to his career, which he wrote about his post “Lessons learned teaching R.”
(23:51) Jim recently wrote a blog post about his experience attending the RStudio Conference at Austin in January, in which he shared several principles for teaching.
(28:35) Jim started working at the KPMG office in Atlanta starting January 2018.
(31:10) Jim talked about his blog post called “Do the simple things first,” in which he argued that “a complex method is never justified until a simple one has been tried first.”
(35:21) Jim talked about the use of machine learning for his projects at KPMG.
(37:03) Jim shared some resources to learn data engineering, including learning SQL and reading “R For Data Science.”
(40:40) Jim shared the key developments in the R ecosystem in 2019 that he’s most excited about, including caret and tidyverse.
(44:46) Jim gave his prediction on how data science will evolve in the next 5 years.
(49:04) Jim anticipated his career trajectory.
(49:49) Closing segments.
His Contact Info
His Recommended Resources
“What’s in a name” from Lyft Engineering Blog
“Thinking, Fast and Slow” by Daniel Kahneman