Pavel Klemenkov
Data Science

Pavel Klemenkov

Current position
Chief Data Scientist (Data Platform) at NVIDIA
Founder of the Moscow Spark tech community
Co-author of “Big Data for Data Engineers” Coursera specialization
Skills
Machine Learning
Python
Software Development

Social

The Courses

  • Big Data Analysis: MapReduce, Spark, BigTable/HBase, Distributed Data Analysis

About

Pavel has graduated from the Lomonosov Moscow State University in 2009, department of Computational Mathematics and Cybernetics. In 2013 he has finished his PhD program. Pavel started his professional career as a software engineer at one of the largest Russian telecom companies Beeline. Then he moved to Rambler&Co, which is the largest Internet media company in Russia. He developed machine learning algorithms for Rambler/News (second largest news aggregator in Russia).

Then he worked as the technical leader for Rambler/News and Rambler/Portal. Last 4 years Pavel worked as the Head of Machine Learning Department at Rambler&Co, supervising machine learning solutions for all kinds of business areas (computer vision, advertising, recommendations, credit scoring). Now he works as the Chief Data Scientist at NVIDIA supervising all machine learning tasks which use telemetry data collected from GPUs all over the world. Pavel is also the founder of the Moscow Spark community which unites several hundred professional users and developers of Apache Spark.

Experience

Chief Data Scientist (Data Platform)
Nvidia
Apr 2018 – Present

Co-author and instructor of the Big Data for Data Engineers Specialization
Coursera
Oct 2017 – Present

Founder
Moscow Spark
Apr 2017 – Present

Head of Machine Learning Department
Rambler&Co
Apr 2014 – Dec 2017

Team Lead of Rambler and Rambler.News
Rambler&Co
Sep 2013 – Apr 2014

Software engineer
Rambler&Co
Aug 2011 – Sep 2013

Software engineer
Vimpelcom
Oct 2010 – Aug 2011

Software engineer
Lomonosov Moscow State University 2007 – Oct 2010

Education

Lomonosov Moscow State University (MSU) Master of Science in Computer Science 2004 – 2009

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