Lead Data Scientist, Revenue - Ads, Revenue

Das ist der Job

Develop practical approaches that improve advertiser performance, marketplace relevance, and business outcomes.

Darum lohnt es sich

Partner with Analytics Engineering, Data Engineering, and backend teams to ensure training data, feedback loops, online signals, and offline datasets are suitable for robust optimisation work. A conscious team player who understands when work touches other team members and proactively aligns with them. Lunch benefit during workdays.

Frequent team‑building events. In this position, you’ll Own optimization logic for Ads systems, handling core problems such as ranking, targeting, pacing, budget allocation, candidate selection, and auction or bidding logic where relevant.

Take charge of model and algorithm development, including prediction, scoring, calibration, exploration/exploitation methods, and constrained optimization suited to Vinted’s marketplace context.

Lead experimentation and performance‑improvement frameworks, defining hypotheses, evaluation methods, and translating learnings into better system behaviour. Guide objective‑function and constraint design, turning product and business goals into tractable optimisation problems and implementable data‑science logic.

Be responsible for Ads performance diagnostics, performing deep‑dive analysis to identify delivery, relevance, auction, supply‑demand, or model issues and propose solutions. Contribute to production implementation in Ads, partnering with engineering and Decision Scientists to move models and optimisation logic from idea to reliable deployment.

Partner with Product Managers, Decision Scientists, Analytics Engineers, and developers to shape advertiser‑facing features and internal optimisation capabilities from a Data‑Science perspective.

Collaborate with Decision Science counterparts and other Data Scientists to ensure optimisation changes are evaluated with appropriate metrics, guardrails, and marketplace context. Help explain system behaviour, performance drivers, and expected impacts of optimisation changes to non‑technical stakeholders when needed.

About You Strong applied machine‑learning and statistical skills. Experience with Ad Tech systems and optimisation problems. Strong product and business judgement. Comfort working on production systems with engineers. Ability to operate effectively in ambiguous, evolving domains.

Experience in ads ranking, auction systems, pacing and budget optimisation, marketplace or recommendation systems, relevance modelling, or other real‑time optimisation environments where multiple objectives must be balanced. Well‑versed in Python and SQL; experience with BigQuery is an advantage.

A structured, meticulous approach when testing new methods toward a set goal. Good at explaining details of machine‑learning methods to lay audiences. Solid written and spoken English. Work perks Share‑options programme. 30 days paid annual leave. Latest MacBook models.

Digital mental and emotional health support and Employee Assistant Programme (EAP). Home‑office support: IT workstation equipment and a personal budget of up to €540 for home‑workplace furniture. Personal monthly budget for shopping on Vinted. Discounted gym membership plan. Pension plan with Vinted matching 150% of your chosen contribution.

Supplemental private health insurance. Life and disability insurance. Subsidised Deutschlandticket for commuting by public transport. Up to 90 days per year of workation (21 days may be spent outside the EU). Dog‑friendly office.

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 race, age, religion or belief, sex, national origin, citizenship, gender identity, sexual orientation, disability, or any other protected characteristic. Salary €90,100—€132,500 EUR #J-18808-Ljbffr