London, New York or Boston
Your role
Data will be central to the success of our company. Using it very well is non-negotiable, and doing it even better will always make a real difference to our users.
As our Founding Data & AI lead, you’ll work closely with the rest of the founding team, focusing on:
- Making our product take the best possible business decisions for users, by designing and building:
- Models that use a blend of heuristics, Gen AI and ML to make decisions and take actions
Measures and tests to monitor and improve performance
- Ways to use the behavioural data of payers and merchants to continuously improve performance
- Intuitive ways for users to influence and control AI decisions
- Developing the overall data architecture and pipelines to feed decisions, including:
- Robust systems to analyse structured and unstructured data from multiple sources in order to produce insights for the decision models
- Ways to effectively manage the entity resolution and integration of structured and unstructured data from multiple sources
- Identification and incorporation of promising new data sources to feed decisions
- Approaches to managing and improving data quality
Like everyone in the founding team, this role will initially focus on making things happen fast yourself, but we’d love you to be there to build a team as we grow the business together. A candidate with the experience and skills to be the long-term data leader as we scale is desirable, but not required.
Requirements
- Hands-on, technically strong individual contributor
- Experience designing and building heuristic and ML models, as well as putting them into production with assistance from engineers
- Experience as the data leader on “zero to one” new product development
- Ability to solve problems with varying levels of data input/availability
- Pragmatic, impact-orientated mindset. A focus on building delightful products that customers love
Bonus points for any and all of the below
- Experience in a startup/scale-up environment
- Experience managing teams of data scientists, engineers or analysts