About The Role
As a Product Analyst in the Anti-Financial Crime (AFC) team, you'll turn fraud, AML and behavioural data into sharp detection logic that stops money laundering, fraud and sanctions evasion before they cause harm. In our AI-native environment, automation handles the repetitive work, so your energy goes where it matters: outsmarting new attacks and building defences that stay ahead of every threat.
Your Mission
Analyse fraud, AML and user behaviour data to find gaps in detection logic and opportunities for rule optimisation.
Study user behaviour patterns to distinguish legitimate activity from fraudulent or suspicious actions.
Design, implement and refine detection rules across the Fraud, AML and Sanctions domains.
Investigate emerging typologies and unknown attacks; propose mitigation strategies.
Continuously improve fraud and disturb rates, balancing detection accuracy against customer friction.
Perform QA on alerts, analyse false positives/negatives, and increase precision.
Collaborate with Product, Engineering and Data Science to enhance risk models,



alerting logic and automation flows.
Leverage AI and LLM-based tooling to accelerate investigations and scale your analysis.
Prepare clear, visualised reports on risk trends, rule effectiveness and ongoing threats.
Your Profile
4+ years of work experience in a product analyst role.
Expert-level SQL – you write complex queries daily and can optimise them without thinking twice.
Advanced knowledge of data visualisation tools.
You already work with AI tools, not just experiment with them — they're part of how you analyse, investigate and ship faster.
Ability to see a business meaning behind the data and communicate it in the clearest possible way (even if it's complicated topic).
Upper intermediate level of English.
Would be a plus
Applied probability theory and mathematical statistics knowledge – A/B tests, causal inference, etc.
Proficiency in using Python for data analytics (ex NumPy, Pandas).
Experienc

📌 Senior Product Analyst (Barcelona)
🏢 Vivid
📍 Barcelona