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Vincent Granville
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  • Issaquah, WA
  • United States
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Vincent Granville's Discussions

How much a blog post or article is worth?

Started this discussion. Last reply by JZ Stafura yesterday. 1 Reply

Let's say a niche digital publisher makes $2 million in yearly revenue, delivers 10 million page views in a year, and generates a 50% profit margin. In short, this is $1 million profit per 10 million…Continue

Python vs Java, 15 Spurious Correlations, and More

Started Jan 26 0 Replies

Another set of great articles:Spurious correlations: 15 examples - Sometimes a correlation means…Continue

How and why to "Talk" to Google's Attribution Algorithm

Started Jan 23 0 Replies

Here I am talking about the Google algorithm that is used to attribute an article to the original blog where it was posted first, rather than to subsequent re-posts from authorized (syndicated) or…Continue

Question about the law of gravity

Started this discussion. Last reply by Vincent Granville Jan 20. 2 Replies

The gravity force is inversely proportional to the square of the distance between the two bodies. Why is the exponent in this formula exactly equal to 2, rather than (say) 1.99997054 or 2.00061833?…Continue

Gifts Received (3)

 

Vincent Granville's Page

Profile Information

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), domains (data science, operations research, machine learning, computer science, business intelligence, statistics, applied mathematics, growth hacking, IoT) and roles (data scientist, founder, CFO, CEO, HR, product development, marketing, media buyer, operations, management consulting).

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, automated exploratory data analysis with data dictionaries, data videos as a visualization tool, automated data science, 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. He also holds a few patents on scoring technology, and raised $6 MM in VC funding for his first startup. 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 here and includes top publications, presentations, and work experience with Visa, Microsoft, eBay, NBC, Wells Fargo, and other organisations.

Follow me on Twitter at @ROIdoctor.
My Web Site Or LinkedIn Profile
http://www.linkedin.com/in/vincentg
Field of Expertise
Analytics, Big Data, Data Science
Professional Status
C-Level
Years of Experience:
15
Your Company:
Data Science Central, AnalyticBridge
Industry:
Internet
How did you find out about DataScienceCentral?
Tim Matteson
Interests:
Networking, New venture, Recruiting, Other
What is your Favorite Data Mining or Analytical Website?
http://www.datasciencecentral.com
What Other Analytical Website do you Recommend?
http://www.analyticbridge.com

Bio

Well rounded, visionary data scientist 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 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.

Latest Activity

Livan Alonso liked Vincent Granville's blog post 5 Ways to Get Fired as a Data Scientist
2 hours ago
Giacomo Snidero liked Vincent Granville's blog post 5 Ways to Get Fired as a Data Scientist
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Matthew Brooks liked Vincent Granville's blog post 5 Ways to Get Fired as a Data Scientist
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Alvaro Marenco liked Vincent Granville's blog post 5 Ways to Get Fired as a Data Scientist
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Judy Edmonds commented on Vincent Granville's blog post 5 Ways to Get Fired as a Data Scientist
"So true. Applies across the board actually. Good post."
yesterday
Judy Edmonds liked Vincent Granville's blog post 5 Ways to Get Fired as a Data Scientist
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Richard Perry commented on Vincent Granville's blog post Data science without statistics is possible, even desirable
"Very silly article. I am a "Data Scientist" but my previous job title was "Statistician". While there are subtle differences, this article a consequence of naivety. The writer sounds a bit like Nassim Nicholas Taleb. I've…"
yesterday
JZ Stafura replied to Vincent Granville's discussion How much a blog post or article is worth?
"Great Article! I would suggest however, that the "army of well-paid editors" at Elsevier is a fiction. Most of the highest-cost article would be in high-impact peer-reviewed journals, which rely on free reviewing (e.g., the heavy lifting…"
yesterday
Dan K. Hansen liked Vincent Granville's blog post How a Digital Transformation Can Improve Customer Experience with Big Data
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Dan K. Hansen liked Vincent Granville's blog post 5 Ways to Get Fired as a Data Scientist
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Alfred liked Vincent Granville's blog post Data science without statistics is possible, even desirable
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Benjamin Bertincourt liked Vincent Granville's blog post 5 Ways to Get Fired as a Data Scientist
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Denis Rasulev liked Vincent Granville's group Tutorials
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Muluken Sholaye Tesfaye liked Vincent Granville's blog post Data Scientist versus Statistician
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Comment Wall (11 comments)

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At 5:05pm on June 21, 2015, Sankara Kumaravel gave Vincent Granville a gift
At 5:28am on June 15, 2015, Lissy Able said…

Hi Vincent,

Can you suggest some points or links about serious data quality issue with the information pulled.

Thanks

Lissy

At 3:38pm on March 11, 2015, Donald Tynes said…

Vincent,

I recently was hired as a data scientist. As a new hire, leading the department of Business Intelligence, I am faced with self-posed questions such as, "What do I need to accomplish in the first 5 days?" And, "What should I accomplish in the first month?" And, of course, "How do I develop a long-term plan for transforming the business into a data-driven organization?" To make the problem of determining how I should focus my attention even more complicated, I have a single employee whom I want to groom to understand the algorithms that I am implementing. Also, I have a CEO who only agreed to hire for this position because the CIO, CFO, and COO encouraged him to do so, but he is highly skeptical of what data science can do for the organization; this complicates matters too because it puts on me a pressure to be dazzling right out-of-the-box. 

I have given these questions considerable thought. I am on day 3 of my new job. I have decided to orient myself on the business' data, query tools, and self-service tools, such as QlikView. I have so many ideas, I have difficulty in choosing a single direction in which I should run. I must note that I want to be significantly impactful while minimizing disruptions in the business' daily functions. To that end, I keep thinking, "run a clustering analysis! Discover the patterns and trends in the company's data to begin the model-building process."

What advice would you give a young data scientist on his 4th day on the job (as it is for me, tomorrow)? 

At 5:22am on December 3, 2014, Harvey Summers said…

I thought you might like this site: http://rpsychologist.com/d3/CI/ 

Interpreting Confidence Intervals

an interactive visualization

At 11:29pm on October 31, 2014, Philippe Van Impe said…

Being from Belgium, you are welcome to join our meetup group about data sciences http://www.meetup.com/Brussels-Data-Science-Community-Meetup/

At 12:21pm on September 25, 2014, Christian Block said…

Hello Vincent, 

I just found DataScienceCentral and wanted to say thank you for putting it together! I'm looking forward to reading through more of the content and checking out your book (which I have ordered).  

Best Regards,

Christian Block

At 6:19am on August 5, 2014, Nasir M. Uddin, Ph.D. said…

Hi Vincent:

This is a great platform to be informed with any latest updates in the field of data science - thank you so much for such a platform.

Regards, Nasir 

At 8:03am on January 8, 2013, Marc Jape said…
Vincent:

This is a great platform that I was not aware of. Keep up the good work.

Regards,
Marc
At 1:05pm on December 19, 2012, Johnny L. Hopkins said…

Thank for the request.

At 12:50pm on September 19, 2012, Paul Jameson said…

Hello Vincent, 

Thanks for the connection. I would like to ask you a question, when I joined here my BIO states (To understand the building blocks based on natural data transfer.) it's very good I like that, but could you tell me how my BIO was achieved? Was it (A) human input or (B) machine?  

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Vincent Granville's Blog

5 Ways to Get Fired as a Data Scientist

Posted on February 3, 2016 at 9:19pm 1 Comment

Guest blog by Justin B. Dickerson, PhD, MBA, PStat, Chief Data Scientist at Snap Advances. 

Okay, that headline was meant to get your attention. But lately, I've been thinking about this crazy circus we call data science and how everyone seems to think data scientists are invaluable, treasured, and potentially "un-fireable" in this age of data scientist negative…

Continue

Groundhogs. I choose to celebrate National Prediction Day

Posted on February 3, 2016 at 8:57pm 0 Comments

Guest blog by Jay Gendron, Associate Data Scientist at Booz Allen Hamilton; Author; Data Analytics; Speaker.

Happy Groundhog Day! Happy National Prediction Day?

In today’s edition of “Coffeehouse Connect” we take a look at a major predictive event in the United States that occurs each year on February 2.

Today is Groundhog Day. It occurs in…

Continue

Weekly Digest, February 8

Posted on February 3, 2016 at 4:30pm 0 Comments

Starred articles are new additions or updated content, posted between Thursday and Sunday. The weekly digest has six sections: (1) Featured Resources and Technical Contributions, (2) Featured Articles and Case Studies, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content.

The full version is always published Monday.…

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How to check hypotheses with bootstrap and Apache Spark?

Posted on January 29, 2016 at 9:30am 0 Comments

Guest blog post by 

There is a featureI really like in Apache Spark. Spark can process data out of memory in my local machine even without a cluster. Good news for those…

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