About the role
Decision Scientist (Data Analyst), VGo Carrier Technology | Vinted Careers Vinted Relocation How We Hire Engineering Academy Data Science & Analytics Academy Marketing Tech Academy Internships Early Careers Blog Vinted Group Vinted Marketplace Vinted Go Vinted Pay Culture at Vinted About en Jobs Decision Scientist (Data Analyst), VGo Carrier Technology Data Science & Analytics Amsterdam, Netherlands Vinted Go Brief info about Vinted Our mission is to make second-hand the first choice, and we're looking for people who want to help us get there. Every day, we work together to help our members buy and sell pre-loved clothing and lifestyle items, giving each piece a second life – or even a third. The Vinted Group is made up of three business units that support this mission: Vinted Marketplace is Europe’s leading platform for second-hand fashion and a go-to destination for all kinds of pre-loved items, with a growing range of categories. Our platform connects millions of members across 20+ markets, helping great items find a new life. Vinted Go enhances the shipping experience with a vast network of over 500,000 pick-up and drop-off points, partnering with more than 60 carriers across Europe, with added services like item verification for peace of mind on high-value pieces. Vinted Pay is the newest part of the Vinted Group, dedicated to bringing secure, reliable payments to buyers and sellers across Europe. Seamlessly integrated into the Vinted app, it helps keep every transaction safe, efficient, and easy for our members. Founded in 2008 in Lithuania, Vinted began as a way for friends to find new homes for clothes they no longer needed. In 2019, we became Lithuania's first unicorn! Today, our headquarters remain in Vilnius, and we've grown with offices across Europe, supported by a team of over 2,000 people. Information about the position As a Decision Scientist at Vinted Go, you will join the Data team at the heart of building the in-house logistics carrier of Vinted. You’ll join the VCarrier DSA Intelligence Team that has another 8 Data colleagues supporting direct Operations and Network Development questions. You‘ll collaborate directly with the Strategic Operations and Planning Team (S&OP). The S&OP team acts as a bridge between commercial growth, financial planning, and physical logistics operations where your primary focus will be to take our current forecasting workflows and scale them for the next stage of growth. You will mature existing forecasting methodologies into automated, code-based pipelines, build robust systems to track and validate forecast accuracy, and continuously identify opportunities to improve these models. At Vinted, we have three distinct roles within 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 Partner with the Strategic Operations and Planning Team to improve their operational forecasting that makes Vinted Go Carrier more efficient. Evolve existing forecasting models into robust, automated, code-based pipelines (Python, SQL, dbt) that can scale dynamically across our European logistics network. Design and implement automated feedback loops to measure forecast accuracy (e.g., comparing planned vs. actual volumes across different hubs, service areas, and timeframes). Partner with Operations and other Decision Scientist in
