Lead Data Scientist, Revenue - Ads

Information about the position

Vinted’s Revenue domain is growing — Ads business is on the mission to develop an advertising ecosystem within Vinted and we’re just getting started. We’re looking for a Lead Data Scientist to join our cross-functional team in Ads to help us make the most of our real estate and evolve toward a high‑performance, privacy‑respectful, in‑house advertising ecosystem over time. Think: an ad of an external partner can generate euros directly but we may well advertise our own Marketplace services or newly launched categories to optimise on net revenue as well as user engagement.

If you have built performance-first Ad optimisation systems and are ready to take on hands-on work while shaping the Data Science roadmaps from a greenfield state - this role is for you.

In this position, you’ll

• Own optimization logic for Ads systems. Own the data science approach behind core Ads optimization problems such as ranking, targeting, pacing, budget allocation, candidate selection, and auction or bidding logic where relevant.
• Develop practical approaches that improve advertiser performance, marketplace relevance, and business outcomes.
• Take charge of model and algorithm development. Design, develop, and iterate models and algorithmic approaches used in Ads delivery and optimization. This may include prediction, scoring, calibration, exploration/exploitation methods, and constrained optimization approaches suited to Vinted’s marketplace context.
• Lead experimentation and performance improvement frameworks. Own the analytical and experimental process for improving optimization systems. Define hypotheses, evaluation frameworks or logic changes and support translating learnings into better system behavior.
• Guide objective function and constraint design. Help define optimization objectives that balance advertiser value, revenue, user experience, and operational constraints. Turn product and business goals into tractable optimization problems and implementable Data Science logic.
• Be responsible for Ads performance diagnostics. Own deep-dive analysis of system behavior and performance degradation. Identify where delivery, relevance, auction dynamics, supply-demand imbalance, or model issues are limiting outcomes, and propose solutions.
• Contribute to Production implementation in Ads. Partner with engineering and Decision Scientists to move models and optimization logic from idea to reliable implementation.
• Partner with Product Managers, Decision Scientists, Analytics Engineers and developers to shape advertiser-facing features and internal optimization capabilities with a clear understanding of feasibility, impact, and tradeoffs from the Data Science perspective.
• Collaborate with Decision Science counterparts and other Data Scientists to ensure optimization changes are evaluated with appropriate metrics, guardrails, and marketplace context.
• Partner with Analytics Engineering, Data Engineering, and backend teams to ensure training data, feedback loops, online signals, and offline datasets are suitable for robust optimization work.
• Help explain system behavior, performance drivers, and expected impacts of optimization changes to non-technical stakeholders when needed.

About you

We are looking for someone who combines:

• strong applied machine learning and statistical skills,
• experience with Ad Tech systems and optimization problems,
• strong product and business judgment,
• comfort working on production systems with engineers,
• and the ability to operate effectively in ambiguous, evolving domains.

The strongest candidates will have experience in areas such as:

• ads ranking,
• auction systems,
• pacing and budget optimization,
• marketplace or recommendation systems,
• relevance modeling,
• or other real-time optimization environments where multiple objectives must be balanced.

• Well-versed in Python and SQL, BigQuery is an advantage
• Have a structured, meticulous way of working when trying out different approaches towards a set goal
• Be a conscious team player who understands when their work touches that of other team members and proactively aligns with them
• Good at explaining details of machine learning methods to lay audiences
• Solid written and spoken English

Studies show that women and members of underrepresented communities often apply for jobs only if they meet 100% of the qualifications. If you don’t recognise yourself in all of the above, you might still be an excellent candidate for this position. If this role excites you, we encourage you to apply.

Work perks

• The opportunity to benefit from our share options programme
• 25 working days of holiday
• Access to all the tools & tech needed for work
• Home office support: we provide IT workstation equipment and a personal budget of up to €540 for home workplace furniture
• Private health insurance
• Digital mental and emotional health support and Employee Assistant Program (EAP)
• Frequent team-building events
• A personal monthly budget for shopping on Vinted
• 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
• In Vilnius office: Gym & in-house meals at friendly prices
• In Kaunas office: a monthly lunch allowance, and a once-a-week provided in-house lunch and breakfast

Working at Vinted

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 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.