The Team
The Greenwich Statistics’ team is...
Greenwich Statistics is managed by a senior management team and high-calibre statisticians and econometricians with diverse backgrounds.
Jeff is an engineer from a leading school in the field of statistics. Hang is maintaining the link between research and innovation. Benoit is specialized in programming. Camille is a doctor in mathematics and is qualified in algebra and optimization. Etienne sets the tone and is the bond between the statistical and business world. Frank offers his experience in training and software migration. The team’s strength is the combination of the diverse expertise with a common statistics thread.
Etienne Costes
Member of Executive Committee and Partner - Greenwich Consulting France
Education: Business school (HEC), MBA from Kennan Flagger Business school
Experience: Telecoms / media - strategy - strategic marketing - client and product marketing - distribution - management
Frank Rimek
Software and Training Director
Education: Agronomic Engineer specialized in statistical methods, ENSAM - MA in Biostatistics, USTL
Experience: Cosmetics - Insurance - Retail - Customers profiling solution
Expertise: Datamining - Modeling - Scoring - Sensometry Analysis - Customer Insight - Statistical Training - Software migration
Ngoc-Hang Khuc
PhD student
Education: MSc in Applied Statistics, University of Rennes, France
Experience: Epidemiology - Effectiveness of the Quebec PCV-7 vaccination program, Energy – Load curves modeling and forecasting
Expertise: Exploratory data analysis – Segmentation/Clustering/Scoring – Time series analysis – Non parametric econometrics
Research: Predictive maintenance in wind energy
Jeff Chau
Economist Statistician
Education: MA in Probability and Statistics, University of La Sorbonne, Paris - Engineer graduated from National School of Statistics (ENSAE)
Experience:Forecasting and Supply – Probability estimation of the power grid cut-off, Pretroleum production modeling, Electricity consumption estimation according to domestic appliances
Expertise: Specialized in segmentation - churn prediction - customers clustering - Econometrics - Bayesian approach - Neural network
Research: Detecting fraud by analyzing Call Detail Records (CDR)
Benoit Thieurmel
Computer scientist Statistician
Education: BA in Computing and Mathematics, University of Brest, France - MSc in Applied Statistics, Agrocampus-Ouest Rennes, France
Experience: Image processing and clustering with IBR (among other methods) in collaboration with the Los Alamos National laboratory, NM, USA
Expertise: Datamining - High dimension analysis - Algorithmic language - Sensometry analysis - Regression
Research: Non-parametric regression and image processing
Camille Mével
R&D Statistical Analyst
Education: PhD in Mathematics, UCBN, Example and applications of quantum groupoids - MA in Statistics, ENSAE
Experience: Electricity consumption forecasting at local resolution - Grid's losses and renewable energy impact on the grid modeling
Expertise: Time series analysis - Non parametric regession - Biostatistics - Mathematics (combinatorics & optimization)
Research: Adaptative splines with low kernel dimension
