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Vinted

C2C marketplace for pre-owned fashion.

Staff Data Scientist - Trust & Safety

Applied Machine LearningPosted on Nov 10
Full-timeKaunas, Kaunas City Municipality, Lithuania€7.7k - €10.4k /mo

About the Job

Requirements

  • Have 8+ years of experience in Data Science, Machine Learning, or a similar role, including significant time owning production models or model evaluation at scale.
  • Have led cross-team technical work without formal authority and be comfortable setting standards that other teams adopt.
  • Have deep expertise in statistical inference and experimentation, including A/B testing, measuring precision and recall under imperfect or biased labels, sampling for ground truth, and causal reasoning.
  • Understand the production machine-learning lifecycle, including evaluation, threshold setting, retraining, drift, feature stores, and monitoring.
  • Have hands-on experience evaluating LLM-based systems, or a strong interest in building rigorous methods for them.
  • Be highly proficient in SQL and Python and comfortable working in a modern data stack such as BigQuery and dbt.
  • Be able to turn messy, cross-system problems into a clear plan and explain trade-offs to technical and non-technical audiences, including senior leadership.
  • Be fluent in written and spoken English.

Responsibilities

  • Design the end-to-end machine-learning architecture for detection, risk scoring, routing, and decision-making.
  • Develop cost-efficient, layered inference strategies that combine broad, low-latency screening with deeper, more expensive analysis where it adds the most value.
  • Establish approaches to continuous risk assessment across the member lifecycle, from registration and listing creation to ongoing activity.
  • Define how to measure end-to-end detection effectiveness, including precision, coverage, missed harm, and computational cost, and use these measurements to identify the highest-impact improvements.
  • Turn siloed, team-level models into a coherent, calibrated detection system by addressing the technical and organisational barriers that lead to local optimisation.
  • Identify and close detection coverage gaps, ensuring relevant signals and outcomes are available for evaluation, diagnosis, and continuous improvement.
  • Set shared technical standards and architectural direction across teams, working with engineering and data science leaders to translate them into production systems.
  • Prototype critical components, test architectural assumptions empirically, and build reference implementations that teams can scale.
  • Explain complex machine-learning trade-offs to senior technical and business leaders as clear choices about harm reduction, cost, and engineering investment.

Desired Qualifications

  • Experience in Trust & Safety, fraud prevention, content moderation, or risk management.

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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