Saad M. Email and Phone Number

- Improving Bell mobile app’s engagement by 200% by building a machine learning model over multiple iterations through marketing campaigns using large datasets related to the Application and website usage.- Reduced time to discover Bell.ca errors on support pages by 15% by using a predictive model to score webpages which helped monitoring the riskiest pages and fix them on time which saved 20k$ per error discovered.

- Improved operational cost efficiency and lowered customer churn through analytical solutions which lead to a revenue boost of 2.5M $ and 4M$ of saved costs over multiple projects involving Bell.ca, Bell and Virgin mobile apps, call centers and customer data.- Improved the company’s reporting and analytical tools by leading new data acquisition and merging for multiples business processes (Orders, TV programming, call centers) and notably the newly acquired Bell Aliant where I overlooked the process from start to finish by leading developers and business analysts to achieve collecting and documenting the data with a minimum loss in quality

Project: BI product implementation for retail and customer loyalty monitoring• Defining KPIs, developing a dashboard and analytical tools for a loyalty program based on transactional, geospatial and social media data. Environment: PostgreSQL, SPSS, Tableau Software

Project: Literature review for an academic business intelligence article Defining effective keyword research methodology based on multiple academic data repositories Using business intelligence methodologies to sort out relevant articles

 Assessing creditworthiness of customers using financial ratios Helping the bank lower its risks by monitoring the evolution of credit risk for new applications