Richard Boire’s experience in predictive analytics and data science dates back to 1983, when he received an MBA from Concordia University in Finance and Statistics.
His initial experience at organizations such as Reader’s Digest and American Express allowed him to become a pioneer in the application of predictive modelling technology for all database and CRM type marketing programs. This extended to the introduction of models which targeted the acquisition of new customers based on return on investment.
With this experience, Richard formed his own consulting company back in 1994 which later became the Boire Filler Group, a Canadian leader in offering analytical and data management services to companies seeking solutions to their existing predictive analytics or database/digital marketing challenges.
OUR UNIQUE VALUE PROPOSITION
We customize solutions to your business needs not customize your business needs to our services and products. Our experience and knowledge has created invaluable expertise in identifying challenges and needs that can be solved through the data science discipline. This is not only about applying the right machine learning or AI algorithm in developing a solution. More importantly, it’s also about creating the right data environment as the necessary fuel for these machine learning and AI algorithms.
THE TEAM: A NETWORK WITH ACCESS TO KEY RESOURCES
Recognizing that the world of analytics is becoming more and more specialized, our value to clients is to be able to identify and understand business problems while integrating the right data in order to create the solution. In many cases, this will require that we work virtually with a number of specialized personnel on a project by project basis. Our business network can quickly gather the right individuals from a variety of different areas:
- Programming in languages such as Java, HTML , Python, R, SAS, SQL, other programming languages.
- Data Management expertise and familiarity with the Hadoop framework of distributed data environments
- Unstructured,semi-structured and structured data environments
- Machine Learning tools and their applicability in solving the business problem at hand