Account Risk Management Analyst, EMEA - Trust & Safety

tform safety and operational efficiency.

• Automate detection and investigation workflows to identify coordinated networks and high-risk account clusters engaged in impersonation, spam, or policy evasion.
• Design and evaluate analytical frameworks that leverage behavioural, device, and graph signals to detect emerging attack patterns and continuously improve system precision and recall.
• Conduct research and development on behavioural signals - identify, design, and validate new features or attributes that improve detection coverage and enforcement precision.
• Fine-tune and operationalize machine learning and anomaly-detection models to assess account-level risk and surface suspicious patterns in near real time.
• Collaborate cross-functionally with Investigations, Applied Science, and Product teams to improve detection signal quality, model inputs, and decision efficiency.
• Communicate insights through concise reports, dashboards, and presentations that drive executive and operational decisions.
• Contribute to continuous improvement of detection and enforcement pipelines through rule refinement, feedback loops, and model retraining cycles.

Qualifications

Minimum Qualifications:

• Bachelor's degree in a relevant field (e.g., Data Science, Computer Science, Statistics, or related discipline) or equivalent experience.
• Atleast 5 years of experience in risk analytics, trust & safety, fraud, or intelligence analysis.
• Proficiency in SQL and Python for data exploration, analysis, and pipeline automation.
• Experience applying ML and anomaly-detection techniques to large, adversarial datasets.
• Experience with graph analytics or entity-resolution techniques for detecting coordinated or linked behaviors.
• Strong communication skills; able to distill complex analytical findings for diverse audiences.

Preferred Qualifications:

• Practical experience applying AI/ML techniques to solve diverse business challenges
• Hands on experience with big data technologies such as Apache Spark and Hive for large scale data processing and analysis.
• Background in trust and safety-focused roles, with a track record of mitigating risks and ensuring platform integrity.
• Strong problem-solving and analytical skills, demonstrated through the ability to deconstruct complex issues, identify root causes, and deliver actionable insights.