Hey, you look like you might be our new  Data Scientist (Analytics), Merchant

Analytics & Data Science

Helsinki, Finland · Stockholm, Sweden · Berlin, Germany

Full-time

About Merchant Group at Wolt

Wolt as a platform focuses on serving three main groups: customers, couriers, and merchants. In a nutshell, the Merchant Group strives to make Wolt an integral part of our Merchant’s daily business. Their core mission is to provide merchants with self-service tools and automation that are useful, efficient, reliable, and delightful to use. 

About the Merchant Analytics Team

Merchant Analytics is an embedded analytics function within the Merchant Group. The team works to unlock insights related to the marketplace and turn them into actionable recommendations that drive the success of merchants at Wolt. While keeping merchants at heart, the analytics team focuses on all kinds of analytics projects that can benefit merchants while ensuring a seamless consumer experience and also supporting Wolt’s marketplace strategy.

About the Role

As a Data Scientist at Wolt, your role involves diving into our data to solve crucial business problems. The scope of this role ranges from diagnosing problem areas to identifying solutions to designing experiments and ultimately influencing decision-making. This is a rare, operational, and actionable data-driven experience. When you join this team, you will be driving action from the frontlines, rather than just doing yet another analytics role.

Our offering to you

• The online delivery platform that Wolt is building will offer you interesting and complex challenges together with the opportunities to create a big impact with your skills. Lots of geolocational and temporal data in real-time combined with differences in the economics and dynamics of the cities we operate in make Wolt both a challenging and so interesting company to practice analytics. 

• You can choose the location from our tech hubs Helsinki, Berlin and Stockholm, or you can work entirely remotely anywhere in Finland, Germany, Sweden and Estonia. You have the chance to decide the ways of working — a hybrid, at the office, or remote within the location above. 💙 Read more about our remote setup

• You would get to work in a company culture where we take ownership beyond the obvious, do common things uncommonly well, we think big but stay humble, do right by people, we treat others kindly and justly, recognize that if we don’t learn, we won’t stay still but fall behind and keep in mind that Luke was Yoda’s greatest achievement. Read more about how we work.

Our humble expectations

• Degree in Mathematics, Statistics, Computer Science, or a related field, or equivalent work experience. 

•  4+ years of experience in an analytics or data science position within an industry or research setting.

• Expertise in statistical analysis, including hypothesis testing, experimentation and causal inference using statistical software packages in Python, R, or equivalent.

• Proficiency in writing structured and efficient SQL queries for large data sets.

• Have prior experience building intuitive data visualizations and dashboards that influence business decisions, utilizing tools like Tableau, Mixpanel, Looker, or similar.

• Relentless pursuit of new ideas and data sources, and have the ability to systematically tackle ambiguous problems with a data-driven, hypothesis-based approach.

Next steps

The position will be filled as soon as we find the right person, so make sure to apply as soon as you realize you really, really want to join us!

The compensation will be a negotiable combination of monthly pay and DoorDash RSUs. The latter makes it exceptionally easy to be excited about our company growing and doing well, as you’ll own a piece of the pie.

For any further questions about the position, you can turn to Product+ Talent Acquisition Partner - Zhanna Filintseva (zhanna.filintseva@wolt.com)

Apply now

Basic information

Attachments

You're welcome to send us supporting docs, e.g. a resume and a cover letter. Please only submit PDF files.

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