Counsello's Team

• Co-founded startupproviding a platform for insurance companies to implement activity-based rewards programs to improve population health
• Contributed to product design features. These include news feed, motivational messaging, setting up of fitness challenges and analytics to be provided to user and insurance companies.
• Designed and implemented the product using a reactive backend microservices infrastructure in Scala based upon the Lagomframework and Cassandra. As part of backend also implemented a streaming service to pull data from FitBit’s Web API.
• Developed a simulation framework to help set points per activity and the value per point

• Interfaced with enterprise clients to understand business problems and develop excel-based budgeting/forecasting solutions in Excel by combining VBA macros and Vena’s core cloud CPM product
• Strategizing and implementing potential cloud data science services that Vena could provide based on customer data stored in Vena’s cloud service. Prototypes included include anomaly detection in accounting data, segmentation and demand forecasting

Data science subject matter expert consulting for major internal and external enterprise clients. Provided advice across all internal initiatives related to data science/data engineering. Interfaced with clients to understand problems and design and implement solutions. Mentored members of analytics team on predictive analytics and how it could be used to benefit their projects

Donation Increase Prediction for SickKids

• Modeled donor behavior to identify those likely to increase monthly contributions if targeted. Telemarketing campaign based on output of model led to a doubling of success rate per call 
• In addition to client data, increased prediction accuracy by integrating exogenous data sources as Environics PRIZM5 segmentation and Environics enhanced census 
• Zero-hassle deployment at client site. Solution seamlessly integrated with client’s existing data structure and systems, allowing them to plug data directly from their existing data sources 

Sales Forecasting

Deployed sales forecasting solution for large automotive client outperforming internal model by over 50%. Model was put in production and used to decide if sales campaign should be launched to meet sales targets 

Time to next purchase modelling

• Developed model for Volkswagen to predict an individual’s time to next purchase. Targeting based on model led to increased marketing effectiveness across all channels 
• Project involved sophisticated data modelling and engineering challenges requiring aggregation and standardization of data across heterogenous datasets 
• Integrated exogenous data sources such as economic data, Environics PRIZM5, Opticks and Enhanced Census datasets to increase prediction accuracy 

Recipe Recommendation Engine

Developed recipe recommendation engine for Kraft using Spark MLIB that increased click through rate by 40%. Service implemented using Scala, Kafka and Spark Streaming to provide real time recommendations  

Managed overall pricing process of Extended Health & Dental plans. This included analyzing data for abnormal claim activities, checking assumptions, developing claims costs, liaising with marketing to price benefit enhancements and developing and publishing rates.

• Conducted Lapse experience study for the entire business unit 
• Conducted research on how to price new product features