PROFILE
FACTS AND EXPERIENCE
Richard Churchman works at Jube.io where he is responsible for developing a proprietary predictive and prescriptive analytics platform that is used in a variety of industries. This course, however, uses entirely open tools and techniques (although you may be interested in our course Real Time Predictive Analytics with Jube and R).
Richard has been working over with predictive, prescriptive and detailed analytics across a variety of industries and can provide meaningful insight into the application of all techniques taught on the course in other problem industrial domains (e.g. AML and CTF). Richard experience spans employers such as Capital One, TSYS, FIS Global and MasterCard, where his experience in fraud prevention systems evolved, oftentimes underpinned by Predictive Analytics.
After a corporate career, Richard founded a company developing fraud prevention systems, which was subsequently acquired by a US cybersecurity company. Richard's latest start-up is, which focuses on.
Richard has trained over, in some of the world's largest corporations, in the use of. Predictive and Prescriptive Analytics, in addition to the implementation of Jube technology (although this course focuses on SQL and R, which is free technology to apply).
Winning Factors
● Price Prediction
● Fraud Prevention
● Credit Risk
● Advertising Technology Bid Optimisation
Specialist Areas:
● Analytical Techniques
● Deep Learning
● Statistical Analytics
❝ Mr. Richard Churchman was extremely knowledgeable and was able to convey his knowledge in a lovely and entertaining manner. ❞
- Senior Business Analyst, Kuwait Finance House
❝ We recently attended a Predictive Analytics training and that was fine but this masterclass takes the wide array of packages available to R to a totally new level. The Predictive Analytics with R masterclass is simply a fantastic program.❞
- Head of IT for a large KSA importer
Learning Sessions
EXPERTISE IN THE FOLLOWING SUBJECTS
Big Data and Analytics
Fraud and AML Solutions
Predictive Analytics with R
R-Project
Big Data and Analytics