Berlin
egor.ignatenkov@gmail.com
+49 151 68626037
http://linkedin.com/in/ignatenkov/en
http://rpubs.com/phat
https://github.com/eignatenkov
A former Software Test Lead with huge interest in data science and newly acquired relevant skills. Higher education in mathematics, analytical mind, fast learner, inventive, quick thinking, good at problem solving. Able to do data analysis, implement algorithms and present results clearly and simply with appropriate visualization. Some of my reports on data science related tasks and algorithms’ implementations can be accessed here: http://rpubs.com/phat.
Specialist, Mathematics, 2001 — 2006
Lomonosov Moscow State University, Department of Mathematics and Mechanics.
Average grade — 4.41 (out of 5). Specialized in algebra and number theory.
Statistical Learning, Stanford University, 2015
Topics include Linear Regression, Logistic Regression, Cross-validation, Regularization, Splines, GAMs, Random Forests, GBMs, SVM, Clustering.
Data Science, Johns Hopkins University, 2014 — 2015
Sequence of nine courses on data science related topics: The Data Scientist’s Toolbox, R Programming, Getting and Cleaning Data, Exploratory Data Analysis, Reproducible Research, Statistical Inference, Regression Models, Practical Machine Learning, Developing Data Products.
Machine Learning, Stanford University, 2014
Topics include Linear Regression, Logistic Regression, Regularization, Neural Networks, SVM, Clustering, Dimensionality Reduction, Anomaly Detection and Recommender systems. Implemented corresponding algorithms in Octave.
Mining Massive Datasets, Stanford University, 2014
Topics include MapReduce, Web-link analysis, Data-streams, Locality-sensitive hashing, Computational advertising, Clustering, Recommender systems, Analysis of large graphs, Decision trees, Dimensionality reduction, SVM, and Frequent-itemset analysis.
Algorithms: Design and Analysis, part I and part II, Stanford University, 2013, 2015
Assignments included implementation of MergeSort, QuickSort, Depth- and breadth-first search in graphs, Dijkstra’s shortest-path algorithm, Kruskal’ and Prim’s algorithms for computing minimum spanning trees, clustering. Did that in Python and R.
Social and Economic Networks: Models and Analysis, Stanford University, 2014
Game Theory, part I and part II, Stanford University, 2013, 2014
Cryptography I, Stanford University, 2012
Diasoft
Moscow, financial software solutions
Configuration Management Lead, February 2013 — December 2014
Lead Technologist, February 2012 — February 2013
Head of Testing Division, Support Division, March 2008 — January 2012
Headed various (from 6 up to 20 employees) testing and support divisions (including subdivisions in Yaroslavl and Cheboksary) of software testers, automated test developers and programmers responsible for reproducing, fixing and testing bugs found by our clients; releasing new versions of Diasoft FA# GeneralLedger, Diasoft FA# Payments and adjacent modules; other testing activities. Had best testing-related KPI results in FA# GeneralLeger Testing Division, had Employee of the Year award.
Tester, Senior Tester, May 2005 — March 2008