Erreiche dein Karriereziel als Data Analyst / Decision Scientist, Lockers bei Vinted in Berlin

Information about the position

The Vinted Go Points domain at Vinted Go is responsible for expanding and maintaining points (parcel lockers & shops that act as pick-up and drop-off points) network for our logistics operations. As a Decision Scientist, you will play a crucial role in optimising locker data usage for analytical purposes, gathering insights, and improving user flows by defining success metrics, conducting A/B tests, and creating insightful dashboards. Your responsibilities include ensuring a comprehensive view of locker performance, enhancing maintenance visibility, performing anomaly detection, and analysing recurring issues. This role also offers the opportunity to develop future capabilities for auto-detecting potential problems and upcoming maintenance needs to proactively address locker performance and user experience challenges.

We have three distinct roles within Data Science & Analytics (DSA). We believe each role can make a similar business impact in different ways, and therefore our salary ranges are the same for all three roles. To understand your role within DSA context better, here are brief descriptions of each role we have in the department:

• Analytics Engineers are responsible for data curation – translating data needs from stakeholders into architecting, building and maintaining efficient & reliable data models and pipelines.
• Decision Scientists are responsible for actionable insights, identifying and sizing opportunities, and automated tools that increase the quality of product and business decisions by applying statistical methods and data-driven decision-making.
• Data Scientists are responsible for identifying algorithmic opportunities, ensuring those opportunities are addressed optimally, and designing, developing, and maintaining production-grade statistical and machine learning algorithms.

In this position, you'll

• Collaborate with your team and direct stakeholders to identify strategic opportunities, answer key business questions, improve, and maintain data products.
• Analyse identified opportunities to understand their scope and impact.
• Propose and implement key metrics that measure business performance, set up monitoring, and proactively flag issues.
• Ensure requests are answered optimally (e.g., in the form of an ad hoc deep dive, experiment, dashboard, or automatically recurring analysis).
• Define the requirements for A/B testing and analyse the results of A/B tests.
• Enable your team and direct stakeholders to independently leverage data for business insights via self-service and dashboarding tools (Looker).
• Closely collaborate with the product manager and help create a roadmap with prioritised hypotheses and analyses.

About you

• Highly results-oriented and comfortable with iterative processes.
• Strong communication skills, capable of presenting results to both technical and non-technical audiences convincingly.
• Proficiency in dealing with technical challenges when building data products.
• Entry to intermediate experience in the field of data analytics, typically 2+ years of work experience or equivalent proficiency.
• Statistical proficiency, including A/B testing and regression analysis.
• Fluent in SQL with practical experience in Python.
• Experience with dashboarding tools such as Looker, Tableau, etc.
• Advantageous: Experience collaborating with cross-functional product teams.
• Advantageous: Background in logistics or e-commerce.

Work perks

• The opportunity to benefit from our share