Jobs at Vinted

Build and maintain a high-throughput, low-latency feature flagging and experimentation platform. Design and operate microservices and APIs, automate flag lifecycle and rollout, ensure performance and reliability using observability tools, collaborate with product and data teams, and contribute clean code and tooling for large-scale experiment execution.

Build and maintain a high-throughput, low-latency feature flagging and experimentation platform. Design, develop, and operate microservices and APIs, automate lifecycle management, monitor performance (Kibana, Grafana, Datadog, Prometheus), and collaborate with Product and Data Science to enable company-wide experiments.

Lead a cross-functional Messaging engineering team (10-12 reports) to extract messaging from a monolith into a domain service, improve product UX, manage 30+ dependencies, maintain technical excellence (SLIs/SLOs), own incident management, drive testing automation, and partner with EPDA (Product, Design, Analytics) to deliver reliable messaging for millions of users.

Lead a cross-functional Messaging engineering team (10-12 reports) to extract messaging from a monolith into a service-oriented architecture, deliver product improvements, manage 30+ dependencies, ensure reliability via SLIs/SLOs and incident management, drive test automation and technical excellence, and mentor and hire engineers within an EPDA setup.

Own and build the technical systems that drive paid growth across Meta, Google and TikTok. Connect ad spend to real-time logistics capacity, create AI- and low-code automations, set up dynamic localized feeds, define tracking and attribution specs, and measure commercial payback like cost per activated parcel shop and payback periods.

Lead the technical stack for paid growth across Meta, Google, and TikTok. Connect ad spend to real-time logistics capacity, build AI-driven automations and dynamic feeds, define tracking and attribution specs (Server-Side GTM, Conversion APIs), and optimize unit economics like cost per activated parcel shop.

Lead shipping strategy and partner management across assigned countries: negotiate contracts, manage carrier performance, optimize costs and operations, run cross-domain shipping projects, and collaborate with internal stakeholders to improve shipping systems and processes.

Lead shipping strategy across assigned countries: negotiate and manage contracts with carriers and 3PLs, own cost negotiations and mid-mile operations, set and monitor partner KPIs, resolve performance and invoice issues, run cross-domain shipping projects, and identify market and startup partnership opportunities to improve cost, service and continuity.

Lead and grow a 4–6 person Data Science and Decision Science team focused on marketing measurement. Own attribution, media-mix, LTV and long-term effect measurement, applying causal inference and statistical modelling. Build scalable, repeatable, self-service solutions and leverage AI tools to speed development. Partner cross-functionally to translate models into budget and marketing decisions while remaining hands-on for high-impact projects.

Lead a 4-6 person Data Science and Decision Science team to build and scale marketing measurement: attribution, media-mix, LTV, experimentation and long-term effect measurement. Drive repeatable, self-service analytics, apply causal inference and AI, partner with marketing stakeholders, and contribute hands-on to high-impact projects.

Lead a team of 4–6 data and decision scientists to own marketing measurement strategy (attribution, media-mix, LTV, long-term effects), scale models into repeatable self-service solutions, apply causal inference and AI to improve measurement, and partner with cross-functional marketing teams while remaining hands-on for high-impact projects.

Lead a team of 4–6 Decision and Data Scientists to own and scale marketing measurement: attribution, MMM, LTV modelling, experimentation, and long-term effect measurement. Build repeatable, self-service analytics using AI and modern tooling, act as hands-on senior sparring partner for complex projects, and partner cross-functionally to turn models into budget and marketing decisions.

Own end-to-end analyses to quantify business impact of frontend platform changes, define and track technical and behavioral metrics, design and analyze A/B tests, partner with engineering and design during discovery, and scale decision-science methodologies across the organization to inform strategic platform decisions.

Work on payments fraud detection by analyzing large datasets, building and evaluating statistical/ML predictors and business rules, running experiments, creating dashboards, monitoring KPIs, and collaborating with product and engineering to improve fraud prevention and payments safety.

Partner with product and engineering teams to provide data-driven recommendations, run experiments and statistical analyses, define and monitor KPIs, build self-service dashboards, and promote best analytics practices to improve Vinted Pay products.

Lead fraud-related analytics and decision science for payments: analyze large datasets, build and validate statistical/ML models, define KPIs, enable self-service dashboards, and partner cross-functionally to optimize fraud detection and payment product safety.

Own data-driven fraud detection and prevention for payments: analyze large datasets, develop and validate statistical tests and KPIs, build dashboards, collaborate with product and engineering, and improve real-time ML predictors, rules, and external signals to protect transactions while minimizing friction for legitimate users.

Work within a cross-functional Vinted Pay product team to drive data-driven decisions. Identify opportunities, run experiments and statistical analyses, define and monitor KPIs, build self-service dashboards, and communicate insights to stakeholders to shape payments product outcomes.

Partner with product and engineering teams on Vinted Pay to deliver data-driven recommendations, run experiments and statistical analyses, define and monitor KPIs, build self-service dashboards, and promote analytics best practices to influence product decisions.

Lead strategy and delivery for an engineering AI platform: set adoption outcomes, build measurement frameworks, deliver integrated AI tools, run trials, ensure platform reliability and security, and manage a portfolio of cross-domain AI initiatives to drive measurable business impact.