Analytics at Wolt is a business-critical competence team that covers business intelligence, data science, and data analytics. In total, we are a team of 60+ professionals working from Finland, Sweden, Germany, and Estonia all united by our excitement to put Wolt’s valuable data assets into everyday use.
Now we are looking for a (Senior) Data Analyst to join our Support Analytics team in Helsinki, Berlin, or Stockholm.
About the Support Analytics team
As the name suggests, our Support Analytics team’s main goal is to deliver an amazing support experience while optimising our operations by providing actionable insights through proper data processing which will allow running exploratory analyses and experiments, eventually quantifying the impact of those actions on the overall business. 💡
As a (Senior) Data Analyst at Wolt, you’ll get to:
• Step up to the challenge and take ownership of the data analytics topics within the product and operations of the Support domain.
• Be the driving force behind the insights that help our business and product teams comprehend Wolt's marketplace dynamics and anticipate long-term trends.
• Contribute to product development by sharing recommendations that make a real impact, using statistical techniques in Python, R or similar.
• Participate in experiments and pilots to test new features or operational processes, own the design and analysis of the experiments
FAQ About the role:
• Will I have to build dashboards? You can go with Python/R notebooks and presentations only but our Looker platform is at the moment the handiest way to share your (scheduled to refresh) results to a bigger audience. We do think traditional BI dashboards are great in monitoring our business and benefit data analysts with automating data visualization work and inspiring new hypotheses/questions.
• Will I spend 80 % or more of my time in data plumbing/wrangling? Analytics Teams at Wolt have both Data Analysts and BI Developers. BI Developers ensure that we gather relevant data and make it accessible in a scalable and trustworthy manner for the Data Analysts. This is to enable the Data Analysts to work more efficiently within the cross-functional Operations and Product teams, helping them to focus on true data analysis and make Wolt truly data-driven by exploratory and evaluative analytics.
• I want to use machine learning methods in my work. Should I pursue the data science path? Many data analysts at Wolt do utilize ML methods in their work. The main difference between a model built by a data scientist and a data analyst is the audience, purpose, and scale of the model. A model by a data analyst should support the product development and decision-making of stakeholders (insights that people can discuss) whereas a model by a data scientist is expected to be deployed and do millions of decisions as part of our product (think personalization or time estimates in our consumer app). So if ML models for you are (just) tools that assist in generating insights then being a data analyst is definitely the path for you. As this role comes with demand forecasting projects, there’ll definitely be room to use statistical and ML methods.
• I’ve never worked in a tech company and done A/B testing. Is this a blocker for me in becoming a data analyst? As we are curious people and have digital products we often conduct controlled experiments (A/B tests, quasi-experiments, etc). Measuring the true business impact of new features or operational changes is fairly challenging, and that’s why a solid grasp of statistics is necessary to truly thrive in this role.
Our offering to you:
• The online delivery platform that Wolt is building will offer you interesting and complex challenges but also 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.
• 3-5 years of experience in a data science or analytics position within an industry or research setting.
• Expertise in statistical analysis, including hypothesis testing, experimentation, and regression analysis 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.
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 (firstname.lastname@example.org)