(Senior) Applied Scientist, Recommendations

Posted 2 Days Ago
Be an Early Applicant
3 Locations
In-Office
Senior level
Food
The Role
Develop and improve recommendation, ranking, and retrieval models for restaurants, dishes, items, and content. Own applied machine learning problems end to end, including problem framing, data analysis, model development, offline evaluation, experimentation, production deployment, and performance monitoring. Balance relevance with diversity, availability, business constraints, and user intent while collaborating with engineers, product managers, and analysts.
Summary Generated by Built In
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.
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 user intent.
  • Collaborate closely with Software Engineers, ML Engineers, Product Managers and Analysts to turn scientific insights into reliable customer-facing products.
  • Evaluate and apply state-of-the-art ML methods where they meaningfully improve recommendation quality, robustness or efficiency.
  • Contribute to a high bar for applied-science practice through technical reviews, knowledge sharing and thoughtful experimentation.
Our humble expectations
  • You have substantial hands-on experience applying machine learning to real-world problems and a track record of bringing models from development into production; a PhD with relevant applied research experience is equally welcome.
  • You have experience with recommendation systems, ranking, retrieval, personalisation, or closely related ML problems.
  • You can independently turn an ambiguous customer or product problem into a well-scoped ML approach, make sound trade-offs and drive it to a measurable outcome.
  • You are proficient in Python and experienced with modern ML frameworks and large-scale data processing.
  • You understand how to evaluate ML systems rigorously, including offline metrics, experiment design and interpreting online results.
  • You communicate complex technical ideas clearly and work effectively with cross-functional partners.
What we offer

You will work on recommendation problems with direct, measurable impact on how customers discover relevant content. You’ll collaborate with experienced scientists and engineers across DoorDash, Deliveroo and Wolt, learning from multiple recommendation systems while helping shape the next generation of the experience.

Together with your lead, you will have the opportunity to create a personalised development plan that builds on your strengths and develops new capabilities.

 
Our Commitment to Diversity and Inclusion

We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.

Skills Required

  • Substantial hands-on experience applying machine learning to real-world problems and deploying models into production
  • Experience with recommendation systems, ranking, retrieval, personalization, or closely related machine learning problems
  • Ability to independently frame ambiguous customer or product problems into well-scoped machine learning approaches
  • Proficiency in Python
  • Experience with modern machine learning frameworks and large-scale data processing
  • Understanding of rigorous machine learning evaluation, including offline metrics, experiment design, and online results interpretation
  • Clear communication of complex technical ideas and effective cross-functional collaboration
  • PhD with relevant applied research experience

Wolt Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Wolt and has not been reviewed or approved by Wolt.

  • Equity Value & Accessibility Corporate postings highlight equity as part of the compensation package, offering ownership potential alongside salary and benefits. Mentions of stock in certain locations indicate accessible participation beyond base pay.
  • Leave & Time Off Breadth Job materials describe generous vacation allowances and strong time‑off policies in several markets. A global parental‑leave policy with top‑ups beyond statutory levels is also cited.
  • Wellbeing & Lifestyle Benefits Materials describe wellness support such as an Employee Assistance Program, fitness or sports perks, and product credits or discounts. Country‑specific allowances and perk platforms add practical lifestyle value in some locations.

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The Company
HQ: Helsinki
8,287 Employees
Year Founded: 2014

What We Do

Wolt is a Helsinki-based technology company that provides an online platform for consumers, merchants and couriers. It connects people looking to order food and other goods with people interested in selling and delivering them. To enable this, Wolt develops a wide range of technologies from local logistics to retail software and financial solutions – as well as operating its own grocery stores under the Wolt Market brand. Wolt’s products include Wolt+ (subscription service for customers), Wolt for Work (meal benefits and office deliveries for companies), Wolt Drive (fast last-mile deliveries for merchants) and Wolt Self-Delivery (service for merchant partners with their own delivery staff). Wolt’s mission is to make cities better by empowering and growing local communities. Wolt was founded in 2014 and joined forces with DoorDash in 2022. DoorDash operates in 29 countries today, 25 of which are with the Wolt product and brand.

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