Arbetsbeskrivning

The Courier Analytics Team at Wolt focuses on solving complex delivery-related logistical and operational challenges, and our objective is to improve Wolt’s logistics efficiency while delivering an exceptional delivery experience for all parties in our 3-sided marketplace.

Data Scientists at Wolt work to uncover insights and turn them into relevant recommendations, driving decisions for the entire organisation. On the Courier team, we are particularly focused on optimising routing and task assignment efficiency, predicting delivery times with higher accuracy, and aiming for a flawless delivery experience for both our couriers and customers to boost retention.

We achieve this by ensuring Courier Group’s product development is rooted in experimentation with the primary goal of delivering impactful results rather than sole features. By analytical deep-dives, impact estimation, and delving deep into observational data to expose hidden trends and untapped opportunities, our Data Scientists serve as objective advisors, helping to decipher the 'why' behind the data, thereby enabling smarter decisions that align with our overall business strategy.

What you’ll be doing

• Take Ownership: Drive the Logistics analytics topics within Courier Analytics, becoming the go-to expert in this critical area.
• Drive Experiment-Guided Product Development: Serve as the catalyst for analytical deep-dives and controlled experiments that illuminate Wolt's complex marketplace dynamics and causal chains.
• Champion Statistical Rigour and a Data-Driven Mindset: Serve as an internal advocate for the crucial role of statistical rigour in data analysis. Your advocacy will foster a culture where data isn't just used, but used wisely, reinforcing the integrity of our decision-making processes.
• Collaborate Across Teams: Work closely with cross-functional teams, including Product, Design, Engineering, and Operations, to integrate data-driven decision-making into their workflows.

Our humble expectations

• 5+ years of experience in an analytics or data science position
• Proficiency in SQL and Python/R, and AI IDE tools
• Hands-on experience in designing and analysing A/B testing, coupled with knowledge of quasi-experimental methodologies
• A strong grasp of core concepts and models for causal inference, enabling you to expose complex cause-and-effect relationships within data
• Prior experience building intuitive data visualizations and dashboards that influence business decisions, utilizing tools like Tableau, Mixpanel, Looker, or similar