Data Analyst

We want to have all sorts of people in our team – people like you and me, and people different from you and me. To be able to work with diverse teammates – when it comes to gender, age, ethnicity, life background, sexual orientation, political views, religion, or any other personal trait – we consciously aim to offer equal opportunity for everyone to work with us. This is because we believe diverse teams make the most thought-through decisions and build things in the most inclusive way.
Join us today to build Wolt together!
Job Description
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 45+ 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 Data Analyst to join us in Helsinki, Berlin, or Stockholm.
A look into the Data Analytics at Wolt
Whereas data science at Wolt focuses on machine intelligence (think machine learning (ML) models deployed to our product & technology) data analytics focuses on human intelligence. What this means is that our data analysts first and foremost strive to gain actionable insights from all available data that support the decision-making in teams they work with. In other words, data analysts are expected to be the objective advisors who base their findings and recommendations on data and solid data analysis methods.
Data analysts at Wolt work as embedded in a team on one particular domain at a time. This means they are working as close as possible where the decisions are made (i.e. in product development teams or marketing or finance etc.) and hence get to participate in decision-making themselves.
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 visualisation work and inspiring new hypotheses/questions.
- Will I spend 80 % or more of my time in data plumbing/wrangling? We hope not but often the data analyst knows best what transformations and derived datasets they need. In those cases the most efficient way is to work with our python/SQL based ETL tooling and do the work yourself.
- I want to use machine learning methods in my work. Should I pursue the data science path? Many data analysts at Wolt do utilise ML methods in their work. The main difference between a model built by a data scientist and data analyst is the audience, purpose and scale of the model. A model by a data analyst should support the decision making of stakeholders (insights that people can discuss about) whereas a model by a data scientist is expected to be deployed and do millions of decisions as part of our product (think personalisation 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.