Vincent Granville

Male

Issaquah, WA

United States

Profile Information:

Company:
Data Shaping Solutions
Seniority:
C-Level
Job Function:
Data Mining, Marketing Databases, Web Analytics, Statistical Consulting, Other
Industry:
Internet
Short Bio:
Well rounded, visionary data science executive with broad spectrum of domain expertise, technical knowledge, and proven success in bringing measurable added value to companies ranging from startups to fortune 100, across multiple industries (finance, Internet, media, IT, security) and domains (data science, operations research, machine learning, computer science, business intelligence, statistics, applied mathematics, growth hacking, IoT).

Vincent developed and deployed new techniques such as hidden decision trees (for scoring and fraud detection), automated tagging, indexing and clustering of large document repositories, black-box, scalable, simple, noise-resistant regression known as the Jackknife Regression (fit for black-box, real-time or automated data processing), model-free confidence intervals, bucketisation, combinatorial feature selection algorithms, detecting causation not correlations, and generally speaking, the invention of a set of consistent robust statistical / machine learning techniques that can be understood, implemented, interpreted, leveraged and fine-tuned by the non-expert. Vincent also invented many synthetic metrics (for instance, predictive power and L1 goodness-of-fit) that work better than old-fashioned stats, especially on badly-behaved sparse big data. Some of these techniques have been implemented in a Map-Reduce Hadoop-like environment. Some are concerned with identifying true signal in an ocean of noisy data.

Vincent is a former post-doctorate of Cambridge University and the National Institute of Statistical Sciences. He was among the finalists at the Wharton School Business Plan Competition and at the Belgian Mathematical Olympiads. Vincent has published 40 papers in statistical journals (including Journal of Number Theory, IEEE Pattern analysis and Machine Intelligence, Journal of the Royal Statistical Society, Series B), a Wiley book on data science, and is an invited speaker at international conferences. Vincent also created the first IoT platform to automate growth and content generation for digital publishers, using a system of API's for machine-to-machine communications, involving Hootsuite, Twitter, and Google Analytics.

Vincent's profile is accessible at http://bit.ly/1jWEfMP and includes top publications, presentations, and work experience with Visa, Microsoft, eBay, NBC, Wells Fargo, and other organisations.
LinkedIn Profile:
http://www.linkedin.com/in/vincentg
Interests:
Networking, New Venture, Other

Comment Wall:

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  • Nene Lawani

    Thanks Vincent! Sorry I missed this earlier...
  • Hina Ranglani

    sir,looking for a answer how
    scaling up for high dimensional data& high speed data streams..
  • Victor Zurkowski

    Dear Vincent,

    I want to let you know that appreciate your posts. Your excursions in data science, number theory, probabilities, experimental mathematics, etc. are thoughtful, provocative, on occasions infuriating opinionated, and never dull. I also admire how prolific you are. 

    Here's to many more blog entries,

    Victor