Ivan Svetunkov
Associate Professor
Lancaster, England, United Kingdom
Summary
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Senior🎓
Top SchoolIvan Svetunkov is an Associate Professor at Lancaster University specializing in demand forecasting, statistical learning, and the development of forecasting software in R. With over a decade of academic and industry experience, he teaches courses across forecasting, predictive analytics and marketing analytics while producing research that translates modern machine learning principles into practical demand-planning tools. He leads practitioner engagement as Marketing Director of the Lancaster Centre for Marketing Analytics and Forecasting, delivering executive training and helping firms implement state-of-the-art forecasting models. Ivan’s work blends fundamental research with hands-on software development and consultancy, evidenced by his openforecast.org project which packages research into usable analytics tools. Trained in management science with strong mathematical and econometric roots from Saint Petersburg, he is comfortable moving between theory, code and commercial decision-making.
11 years of coding experience
15 years of employment as a software developer
Candidate Economics, Candidate Economics at Saint Petersburg State University of Finance and EconomicsExchange student Business Administration and Management General, Exchange student Business Administration and Management General at HeliaDoctor of Philosophy (Ph.D.) Management Science, Doctor of Philosophy (Ph.D.) Management Science at Lancaster University
English, Russian, French
Stackoverflow
21reputation
6kreached
2answers
1question
Github Skills (94)
exponential10
python10
office36510
regression10
ets10
exponential-smoothing10
prediction10
forecast10
statistics10
econometrics10
regression-models10
statsmodels10
espn10
adam10
r-package10
Programming languages (11)
Github contributions (5)
config-i1/legion
Feb 2021 - Jan 2023
Contributions:1 release, 115 commits, 6 PRs in 1 year 11 months
forecastingtime-seriesmachine-learningmultivariate
config-i1/smooth
Jan 2016 - Jan 2023
The set of functions used for time series analysis and in forecasting.
Contributions:27 releases, 1 review, 2135 commits in 7 years 1 month
regressionforecastingsmoothingtime-series-analysisarima
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