Kevin Kindall Email Address

Senior Data Scientist

EDF Trading is a wholesale energy market specialist.

A quantitative analysis expert with over 20 years of experience in the energy industry, my career has largely been spent on trading floors supporting the front, middle, and back offices. I have built and managed quantitative teams that create solutions to complex business problems from first principles. The business problem set is quite large and diverse, and covers topics ranging from investment appraisal, corporate hedging strategies, option pricing, and monte carlo risk measures to more common problems such as trader spreadsheet design, system of record issues, and price uploads. Although well-schooled in financial theory, my focus has always been to develop sustainable and transparent solutions in a cost effective manner without unnecessary complexity. I also specialize in management presentations where key findings of studies and analysis are presented in nontechnical terms that facilitate both listener comprehension and decision making. I am an active equity trend trader using principles similar to Nicolas Darvas with a 10 year pretax return that averages 30%. I joined Hartree Partners in late 2017 as a Senior Data Scientist. Prior to joining Hartree, I held positions at EDF North America, the Alliance Risk Group, ConocoPhillips, FPL Energy, and Enron. A frequent conference speaker, I have coauthored articles for the GARP Risk Review and Energy Risk Magazine that feature a few of the solutions created over the years. My professional memberships include the IECA, and I am a former member of the Alumni Relations Board for the Tepper School of Business. I have a PhD in Physics from Clemson University, and a MS in Computational Finance from Carnegie Mellon University. Contact information: 281 798 5039 (cell); kkindall@yahoo.com Key skills: derivatives pricing, trade floor support, market risk, credit risk, operational risk, software development, management presentations, problem solving, quantitative analysis, time series, statistics, monte carlo