Join Vinted's Category Experience team, where we drive Vinted’s expansion into new categories and the improvement of existing ones. The team focuses on understanding, developing  and expanding the structure of our catalog. The team works closely with Product teams across Vilnius and Berlin to ensure that our category tree and navigation tools fulfill the needs of our members and are easy to use. As a Decision Scientist in this team you will drive data-informed decisions to enhance the member experience with catalog.

Next to the Category Experience team, you will be a part of the cross-domain Data Science & Analytics (DSA) guild where you will interact and learn from all data people in Vinted.

• Partner with your team and stakeholders to identify strategic opportunities, answer critical business questions, and provide data-driven recommendations that improve category structures, taxonomy design, and member experience.
• Co-create and support the product experimentation roadmap by defining A/B testing requirements, ensuring appropriate tracking is in place, and analysing test results to validate opportunities, measure business impact, and inform decision-making using statistical methods and visualisation tools.
• Select, calculate, and monitor key performance indicators and behavioural metrics, proactively flagging issues and uncovering insights through deeper analysis.
• Collaborate with Taxonomists to enable them to use a data-driven approach to Taxonomy Design and category structure
• Support the Ontologies Platform (engineering) team to answer their data analytics questions 
• Communicate findings, insights, and recommendations clearly to relevant stakeholders, while contributing to a data-driven culture by promoting analytics best practices and helping teams make better decisions with data.

• Experience as a Decision Scientist, Analyst, or other role with a strong data component (typically 2+ years of working experience).
• Experience with designing and running product experiments (A/B testing), knowledge of statistical modelling, probability theory (bonus: experience with causal inference methods).
• Strong business results orientation with the ability to connect scientific approaches with pragmatic problem-solving.
• Strong communicator who can convincingly present results to both technical and non-technical audiences.
• Proficiency in SQL and Python.
• Experience with BI tools (e.g., Looker, Tableau, Power BI).
• Excellent written and spoken English.

• The opportunity to benefit from our share options programme
• 30 days of paid annual leave
• Newest MacBook models
• Digital mental and emotional health support and Employee Assistant Program (EAP)
• Home office support: we provide IT workstation equipment and a personal budget of up to €540 for home workplace furniture
• Lunch benefit per your workday
• Frequent team-building events
• A personal monthly budget for shopping on Vinted
• Access to a discounted gym membership plan
• Pension Plan with Vinted matching 150% of your chosen contribution
• Supplemental Private Health Insurance
• Life and Disability insurance
• A subsidised Deutschlandticket for your commute to the office by public transport
• The opportunity to spend up to 90 days per year - 21 of which can be spent working outside of the EU - on workation
• A dog-friendly office

Individual Learning Budget

We invest in your professional growth! As part of our commitment to continuous learning, we offer an annual learning budget to support your personal and career development through courses, certifications, workshops and more.

Hybrid Work 

We’ve adopted a hybrid workplace model where 2 days in the office are recommended but not enforced. It’s up to you and your team to decide on the exact days you’ll spend working together in person.

Equal Opportunity

The Vinted Group is committed to building an inclusive workplace where people from all walks of life feel a sense of belonging. We welcome applications from people of all backgrounds, identities and life experiences. At Vinted, all applicants are treated fairly without regard to their race, age, religion or belief, sex, national origin, citizenship, gender identity, sexual orientation, disability, or any other protected characteristic.