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Vinted

C2C marketplace for pre-owned fashion.

Lead Data Scientist - Revenue, Ads

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBerlin, Germany

About the Job

Requirements

  • Strong applied machine learning and statistical skills.
  • Experience with advertising technology systems and optimization problems.
  • Strong product and business judgment.
  • Comfort working on production systems with engineers.
  • Ability to operate effectively in ambiguous, evolving domains.
  • Well-versed in Python and SQL.
  • Able to explain details of machine learning methods to lay audiences.
  • Solid written and spoken English.

Responsibilities

  • Own the data science approach behind core Ads optimization problems, including 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.
  • Design, develop, and iterate models and algorithmic approaches used in Ads delivery and optimization, potentially including prediction, scoring, calibration, exploration/exploitation methods, and constrained optimization approaches suited to Vinted’s marketplace context.
  • Own the analytical and experimental process for improving optimization systems by defining hypotheses and evaluation frameworks or logic changes, and supporting translation of learnings into better system behavior.
  • Help define optimization objectives that balance advertiser value, revenue, user experience, and operational constraints; translate product and business goals into tractable optimization problems and implementable data science logic.
  • Own deep-dive analysis of system behavior and performance degradation; identify delivery, relevance, auction dynamics, supply-demand imbalance, or model issues limiting outcomes, and propose solutions.
  • Partner with engineering and Decision Scientists to move models and optimization logic from idea to reliable production implementation.
  • Partner with Product Managers, Decision Scientists, Analytics Engineers, and developers to shape advertiser-facing features and internal optimization capabilities, assessing 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 support robust optimization work.
  • Explain system behavior, performance drivers, and expected impacts of optimization changes to non-technical stakeholders when needed.

Desired Qualifications

  • Experience in 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.
  • BigQuery experience.

About the Company

Vinted

C2C marketplace for pre-owned fashion.

Vinted is an online marketplace where people buy and sell second-hand clothing and accessories. It operates as a consumer-to-consumer (C2C) platform that lets individuals list pre-owned items for sale and others purchase them. Revenue comes mainly from a Buyer Protection fee charged on each transaction, which covers customer support, shipping tracking, and refunds. The platform targets those interested in affordable, sustainable fashion and the circular economy, appealing to users who want to declutter, discover unique items, and shop more environmentally friendly. Vinted’s approach centers on peer-to-peer re-commerce, offering a simple way to trade clothing within a global community, with a focus on accessibility and sustainability rather than new-product manufacturing.

Company size
1,001-5,000
Company stage
Private
Total funding
$559.6M
Headquarters
Vilnius, Lithuania
Founded
2008

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