Expanding the functionality and analytical capabilities of a savings solution for education- ON-414Desired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences, Mathematics, Statistics / Actuarial sciences
Project Length: 6 months to 1 year
Preferred start date: 01/26/2021
Language requirement: English
Location(s): ON, Canada
No. of positions: up to 3
About the company:
payd is North America's education focused savings solution. payd leverages both student's and their parent's financial behaviours to help pay off and save for education with ease. The payd platform allows user to utilize card-linked purchase rounding, cash-back incentives, investment opportunities with Questrade and crowdsourcing savings with family members.
Please describe the project.:
A minimum viable product (MVP) of the payd platform has already been built.
The scope of the project is to expand on the features and analytic capabilities of the payd mobile app. The goal of these capabilities would be to streamline the money moving process with payd’s partners, be scalable and comply with jurisdictional regulatory requirements as payd scales to other jurisdictions. The analytics capabilities will also allow payd to leverage AI to develop recommendation engine for financial literacy based on user spending and saving habits.
Mobile Application Development
- Develop function to allow users to boost savings in a one-time lump sums by applying extra bank funds towards their student debt and education savings. This will enable data to be collected to build analytics to identify when users use this function to put side hustle cash towards their debt. The applied research need is how to develop a scalable framework where the process to move money from payd platform to their partners are secure, streamlined, and scalable (taking into consideration different financial partners and regulations in money movement in different jurisdiction).
- Develop function and necessary APIs that will allow users to convert loyalty points to dollars and apply them to their student debt. The applied research need is how various points-to-dollar formula and how they may change over time from the vast loyalty programs can be streamlined.
- Allow current supporters to apply their total savings to multiple users. Current capability only has multiple supporters to a single user
- Build user analytics dashboard to identify user (students) spending habits, areas to save and alternative options. Outcome is comprehensive analytics that will help student identify where they can save more money, best merchants to work and partner with to ensure more money is going back into student pockets.
- Build analytics to identify when students use function to put side hustle cash towards their debt
The above mobile application development and analytics will allow payd to leverage AI to develop a backbone of a recommendation platform on financial literacty to our users based on their spending habits and saving patterns.
Experience in software development, AI/ML algorithm development, computer science, financial background