Vincent Granville is an innovator and skilled business-owner in the data analysis field and is devoted to creativity and the constant rethinking of concepts.


  • Executive Data Scientist, Co-Founder, Managing Partner

    at Data Science Central

    May 2012 - at Present


    Author, mathematician, open patent inventor, innovator, and investor. Also co-founder of, and founder of

  • Founder and Managing Partner

    at Data Shaping Solutions LLC

    December 1999 - at Present


    Initially a consultancy with clients such as Visa, Microsoft, and eBay, Data Shaping Solutions experienced a new life starting in 2015, becoming a data science think tank, intellectual property and idea foundry, with a focus on automated data science, machine-to-machine communications, robust black-box machine learning algorithms, and statistical / probabilistic number theory research, with applications to Blockchain, Fintech, cryptography, and quantum computing.

  • Chief Scientist

    at LookSmart

    April 2010 - March 2012


    Keyword and search analytics using machine learning and pattern recognition: • Created the list of top commercial keywords that account for 85% of all advertising revenue on Google. • Implemented and programmed the Google AdWords API to automatically find millions of new high value / high volume keywords for advertising campaigns (Perl, SOAP, XML) • Taxonomy improvement. • Click fraud detection (click jacking and Botnet detection). • Web site scoring, with scores used to predict chances of conversion or sales, using hidden decision trees / Naïve Bayes and web crawling. • Automated bidding for advertiser campaigns based either on keyword or category (run-of-site) bidding. • Reverse engineering of keyword pricing algorithms in the context of pay-per-click arbitrage. • Creation of multi-million bid keyword lists using extensive web crawling. Identification of metrics to measure the quality of each list (yield or coverage, volume, and keyword average financial value).

  • Co-Founder and Chief Science Officer

    at Authenticlick

    June 2006 - May 2008


    VC-funded startup. Prototyped automated bidding and click/keyword scoring solutions for search engines, ad networks and advertisers. Worked with the engineering team to implement HDT (hidden decision tree) algorithms. Worked on score standardization and IP blacklist/whitelist architecture. Developed patent-pending statistical technologies and other intellectual properties. Presented at Ad-Tech and the American Statistical Association conferences. Helped win several deals (Microsoft, against large competitors (including Fair Isaac), through proof-of-concept blind tests. Identified major Botnet.

  • Data Mining, and Click Fraud Expert

    at InfoSpace

    January 2005 - June 2006


    Click scoring technology, query intelligence, web analytics, business intelligence related to mobile search. Designed click fraud detection algorithms to process billions of clicks. Created rule selection and rule discovery system for fraud detection, based on machine learning (unsupervised clustering), design of experiments, robust cross validation and linkage with external data sources (Google search results) to discover additional fraud patterns. Enhanced keyword taxonomies using data driven algorithms to detect keyword associations. Defined and tested metrics for keyword correlations. Developed multi-threaded web crawler to feed text mining algorithms with rich, targeted data sources related to local search and / or yellow pages.

  • Data Mining Consultant

    at Wells Fargo

    June 2004 - November 2004


    Detected abnormalities in traffic monitoring systems resulting in a major fix in the Tealeaf reporting system. The bug resulted in visitors and web session statistics to be wrong for all big vendors relying on multiple servers, with visitor session data collected across multiple servers broken down by error in multiple sessions / multiple users.

  • Visa Senior Fraud Consultant

    at Visa

    February 2003 - May 2004


    Developed proprietary feature selection system (200x faster than SAS Enterprise Miner) to detect first instances of fraud and horizontal (single ping) fraud in real time. Production of US zip code maps showing fraud simultaneously in the time, location, recency and volume dimensions. SAS, Perl, C, R, Splus.

  • Senior Statistician

    at CNET

    June 1996 - May 2002

    New York

    Web analytics. Attribution modeling using time series techniques. Inventory forecasting (NBCi). Price elasticity modeling. Web scraping. Advertising mix optimization for both NBC Internet (NBCi) and CNET. Customer profiling. User retention, churn, survival models. Data Warehousing. Web traffic forecast (with automated alarm system to notify product managers of traffic abnormalities). Automating production of various reports (dashboard, quarterly reports for financial analysts). KPI design.

  • Research Fellow

    at NISS

    July 1995 - June 1996

    North Carolina

    Environmental statistics. MCMC. Hierarchichal Bayesian models. Clustering. Storm modeling (time series, spatial processes). Hanford nuclear reservation: risk analysis using space / time models to detect radioactive leakage into the nearby Columbia river (funded by the EPA.) Simulation of bivariate exponential distributions.


  • Post doctorate, Statistics

    at Cambridge University

    1995 - 1996 (1 year) Cambridgeshire

  • Doctor of Philosophy - PhD, Mathematics and Statistics, Summa Cum Laude

    at Facultés universitaires 'Notre-Dame de la Paix'​

    1988 - 1993 (5 years) Bruxelles-Capitale


  • English Native

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