Senior Applied Scientist - Recommendations

About Wolt

Wolt builds technology that enhances ease, enjoyment, and earning opportunities for neighborhoods worldwide. Since our start in 2014 delivering restaurant meals, we have expanded to deliver nearly anything and now operate in more than 500 cities across 30 countries. In 2022, we merged with DoorDash, combining efforts to grow and innovate globally.

Working at Wolt presents challenging and exciting opportunities to learn, build, and ship impactful products. If you are a motivated self-starter with an entrepreneurial mindset, this role offers an inspiring career journey.

As part of DoorDash, we operate one of the largest local commerce platforms globally. Our team focuses on providing personalized recommendation systems to connect customers with the most relevant restaurants, dishes, and products.

Role Overview

We are seeking an Applied Scientist to enhance machine learning models powering our recommendation systems. This role involves solving complex applied ML challenges where model accuracy, product direction, and customer experience are deeply interconnected. Responsibilities encompass all stages from problem definition and data exploration to experimentation, deployment, and assessing customer impact.

Key Responsibilities

• Design, develop, and enhance models for recommendations, ranking, and retrieval to present customers with relevant restaurants, dishes, items, and content.
• Manage end-to-end applied ML projects: define problems, analyze data, build models, set offline evaluation metrics, conduct experiments, and monitor live system performance.
• Create techniques that optimize relevance while accommodating product goals, user diversity, availability, business rules, and evolving user intentions.
• Work closely with software engineers, ML engineers, product managers, and analysts to translate scientific findings into dependable, customer-centric products.
• Integrate state-of-the-art ML methodologies when they significantly boost recommendation quality, robustness, or computational efficiency.
• Maintain high standards of applied science through code reviews, sharing knowledge, and designing rigorous experiments.

Qualifications and Expectations

• Extensive practical experience applying machine learning to tangible challenges with a history of moving models into production; candidates with a PhD and relevant applied research background are encouraged.
• Expertise in recommendation systems, ranking, retrieval, personalization, or similar machine learning domains.
• Ability to independently translate unclear customer or product challenges into scoped ML solutions, balance trade-offs wisely, and achieve measurable results.
• Proficiency in Python and familiarity with contemporary ML frameworks along with large-scale data processing capabilities.
• Strong skills in ML system evaluation, including offline metrics interpretation, experiment design, and online result analysis.
• Effective communication skills to clearly convey complex ideas and collaborate with cross-functional teams.

What We Offer

Engage with impactful recommendation problems that directly influence how customers discover relevant content. Collaborate with seasoned scientists and engineers from DoorDash, Deliveroo, and Wolt to gain insights from various recommendation systems and contribute to future innovations.

Alongside your lead, you will co-develop a personalized growth plan targeting your strengths and fostering new skills.

Diversity & Inclusion Commitment

We are dedicated to fostering a more inclusive workplace by recruiting and supporting diverse teams representing varied backgrounds and perspectives. We believe true innovation arises when everyone is included and provided with resources and opportunities to excel.