(Senior) Applied Scientist, Recommendations
About this role
About Wolt
At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we're building the delivery of (almost) everything and you'll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe.
Responsibilities
- Design, develop and improve recommendation, ranking and retrieval models that surface relevant restaurants, dishes, items and content to customers.
- Own applied ML problems end to end: frame the problem, analyze data, develop models, define offline evaluation, run experiments and monitor production performance.
Requirements
- Develop methods that balance relevance with product and customer needs, such as diversity, availability, business constraints and changing
About Wolt - English
At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we're building the delivery of (almost) everything and you'll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn't always easy, but it's definitely exciting. Here you'll learn more, build more, and ship more than in most other companies. You'll be challenged a lot, but also have a lot of fun on the way. So, if you're a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. Wolt is part of DoorDash - together we form one of the world's largest local commerce platforms. We build recommendation systems that help customers discover the most relevant restaurants, dishes and items throughout their Wolt experience. We are looking for an Applied Scientist to advance the machine learning models behind these experiences. You'll work on challenging applied ML problems where model quality, product decisions and customer experience are tightly connected. This is an opportunity to take ideas from problem framing and data analysis through experimentation, production deployment and measurable customer impact. What you'll be doing Design, develop and improve recommendation, ranking and retrieval models that surface relevant restaurants, dishes, items and content to customers. Own applied ML problems end to end: frame the problem, analyze data, develop models, define offline evaluation, run experiments and monitor production performance. Develop methods that balance relevance with product and customer needs, such as diversity, availability, business constraints and changing