Senior Analyst, Account Risk Management, EMEA - Trust & Safety

Responsibilities

The Account Risk Management team safeguards TikTok's ecosystem by proactively identifying, mitigating, and preventing account-level abuse.
The team combines behavioral, device, and network intelligence with automation and applied machine learning to strengthen the integrity of the platform and reduce risk at scale. Our solutions are designed to detect and disrupt sophisticated threats while ensuring a secure and trustworthy experience for users.

About the Role
We are looking for a Senior Analyst with an applied scientist mindset to join the Account Risk Management team. This is a senior individual contributor role with meaningful ownership and authority. You'll design large scale enforcement systems - developing novel signals, running experiments, and deploying ML driven solutions to identify malicious networks and coordinated networks at scale.
This role requires someone who approaches problems with scientific rigor - forming hypothesis, building measurement frameworks, and iterating through experiments. You'll balance research depth with business impact and build solutions that will scale across billions of users.

Responsibilities
- Design enforcement systems from the ground up by developing novel behavioral, device, and graph signals to identify coordinated networks and adverserial actors at scale.
- Research emerging atatck patterns investigate new adversarial behaviors, prototype detection approaches, and validate signal effectiveness through rigorous analysis.
- Evaluate, fine-tune and integrate machine learning and anomaly-detection models to assess account-level risk and surface suspicious patterns in near real time.
- Conduct research and development on behavioral signals - identify, design, and validate new features or attributes that improve detection coverage and enforcement precision.
- Contribute to continuous improvement of detection and enforcement pipelines through rule refinement, feedback loops, and model retraining cycles.
- Communicate insights through concise reports, dashboards, and presentations that drive executive and operational decisions.

Qualifications

Minimum Qualifications:
- Bachelor's degree in Computer Science, Statistics, Data Science or related quantitative field
- Atleast 5 years of experience trust & safety, fraud detection, or threat intelligence.
- Strong 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 written and verbal 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 distributed computing frameworks (Spark, Hive) for large scale data processing.
- Background in trust and safety-focused roles, with a track record of mitigating risks and ensuring platform integrity.
- Publication or presentation history demonstrating analytical depth.
- Experience designing and running controlled experiments in production systems.