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 Wolt Market Analytics team in Helsinki, Berlin, or Stockholm.
As a part of the advertised role, you’ll work closely with two teams within Wolt Market:
🛍️ Inventory Management team is responsible for the unified supply chain picture;
📲 Store Operations team focuses on finding the most efficient ways of operating the dark stores.
In both of these teams you’ll be able to get your hands dirty with demand forecasting, inventory planning, optimal staff allocation, and other exciting topics. You will derive insights using statistical techniques, and will have a direct contribution to improving the business metrics!
What is Wolt Market:
Wolt Markets are delivery-only grocery stores making shopping incredibly easy. From our dark stores, our customers get everything from fresh produce to household items delivered to their doorstep in 30 minutes - with only a few clicks.
Launched in Helsinki in 2020, today we have several dozens of stores across Wolt Markets. We have dedicated teams: from engineering and design to store operations and inventory management ones – all pushing the boundaries to deliver an amazing customer experience.
As we’re still in the very early stages of our growth, there are plenty of opportunities to build Wolt Market vertical and see the growth journey within online grocery! In this domain, you’ll get exposed to the end-to-end process of running a quick commerce business: from optimizing the supply chain to improving consumer experience.
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 Wolt Market’s Inventory Management and Store Operations teams.
• Empower more junior data analysts, mentoring them to tackle complex data analysis challenges.
• 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.
• 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)