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Trustpilot is a profitable, high-growth FTSE-250 company and the world's largest open customer review platform with over 350 million reviews and 60 million monthly active users. The Trust Applied AI team uses advanced modeling to safeguard the integrity of online reviews and protect the platform from fraudulent activity.
You will join the Trust team as an Associate Data Scientist, working alongside software developers, product managers, ML engineers, and designers to develop, deploy, and maintain innovative models at scale. Your responsibilities will include:
- Build and fine-tune language models, sequence models, graph-based models, and other advanced ML architectures for fraud detection and fake review identification
- Develop, maintain, and deploy production-ready ML models in collaboration with other data scientists and with tooling support from ML engineers
- Work across the business with Technology and Product teams to influence strategic initiatives through applied AI advancements
- Leverage market-standard tools including Google Cloud Platform (BigQuery, Agent Platform tools) and leading data science frameworks for model building and deployment
- Contribute to keeping Trustpilot at the forefront of innovation in fake review detection
You will work with production systems from day one, handling large-scale datasets from a tech platform with behavioral data and fraud detection challenges. The role offers opportunities to develop your career in a diverse, international team.
REQUIREMENTS:
- Hands-on experience developing and deploying ML models on cloud infrastructure (GCP preferred)
- Strong technical foundation in data preparation, exploration, and modeling using Python and SQL
- Demonstrated experience with production-ready ML model development and deployment
- Experience with advanced statistical techniques and machine learning methods, particularly: high-precision classification, graph neural networks, graph algorithms, fine-tuning large language models, handling large label sets with varying quality, and adversarial machine learning
- Experience working with large datasets, ideally from tech platforms, e-commerce, or SaaS businesses; knowledge of behavioral data and fraud/misbehavior detection at scale is a plus
- Excellent written and verbal communication skills
- Willingness to specialize in fraud detection domain and develop cloud engineering skills
- Adaptable mindset and ability to work collaboratively as part of a larger team
