MVF Innovation, Technology & Agility

What project are you most excited to work on in 2025, and what is particularly compelling about this work for you?

The project I’m most excited about is AI-driven product recommendations. What makes it so compelling is that it taps into several areas I’m very interested in as a technologist. It combines data analysis and machine learning on large datasets with intuitive front-end design. The project delivers personalized product recommendations based on historical customer data and past purchasing patterns, providing MVF telemarketers with actionable insights. Ultimately, it helps match the best-fit products with our customers’ needs.

What does the roadmap for this project look like? Who will you collaborate with, and what challenges will you need to overcome in the process?

The roadmap begins with a discovery phase, where we’ll analyze multi-channel customer interaction data to identify ways to train AI/ML models for extracting meaningful insights. From a UI perspective, we need to design ways to make our product recommendations both intuitive and engaging for our internal and external users.

Achieving this will require close collaboration between back-end, front-end and data engineering teams, as well as product and telemarketing teams. The main challenge will be ensuring smooth coordination and alignment across these teams to meet our delivery timelines. However, these challenges can be addressed through clear planning, well-defined roles and responsibilities and iterative functionality releases for stakeholder review and feedback.

What in your past projects, education or work history best prepares you to tackle this project? What do you hope to learn from this work to apply in the future?

My background leading data analysis, machine learning and front-end design teams gives me the confidence to tackle this project. I have previously worked with large customer datasets, using machine learning algorithms to uncover insights that improve user engagement and click metrics. I’ve implemented a recommendation engine for real estate products, which gave me hands-on experience in both the technical and UX aspects of a similar project.

My leadership experience in cross-functional teams allows me to collaborate across business, engineering, product and marketing teams. I’ve managed projects that required alignment between back-end and front-end development, ensuring smooth communication and efficient timelines, skills that will be crucial for this project’s success. I hope to improve my knowledge of applying AI/ML to real-world business problems and further enhance my ability to design intuitive user interfaces that drive user engagement.