Responsibilities
About the team
Ecommerce's Governance and Experience is a global team responsible for ensuring our marketplace is safe and trustworthy for not only users but also sellers and creators. We value user satisfaction and work on policies, rules, and systems to ensure quality. As the Anti-Fraud Data Analytics Manager, you will lead a global team to generate actionable insights, define key metrics that shape fraud management strategies, and evaluate trade-offs between risk mitigation and customer experience.
Roles & Responsibilities:
- Own and drive the antifraud data analytics team's strategy and OKRs.
- Lead, build, and retain a high-performing team of Data Analysts.
- Mentor and guide the team in solving complex analytical problems related to risk and fraud management.
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- Anticipate risks and analyse fraud trends across global markets, developing intelligence systems for mitigation.
- Leverage analytics to optimise fraud strategies, improving precision and increasing detection rates.
- Collaborate and influence stakeholders across business lines, product development, and operations to ensure fraud considerations are integrated.
- Lead large-scale, cross-functional analytic projects, prioritise tasks, and translate business requirements into actionable strategies.
- Define and standardise key performance metrics, building robust reporting models for effective tracking, evaluation, and continuous improvement.
Qualifications
Minimum Qualification
- At least 5+ years of data related experience in one of the following areas: Antifraud, Risk Management, Trust & Safety, eCommerce or Tech industry in general.
- Bachelor's degree or above with a background in Computer Science, Business Analytic, Math, Statistics, or related field.
- At least 3 years of experience in a people management role.
- Data driven with strong analytical ability to develop clear insights.
- Experience with SQL and analytical tools (SAS, R, Python) is a must.
Preferred Qualification
- Strong interpersonal skills with the ability to build relationships and effectively liaise with people at all levels.
- Excellent data visualisation and storytelling skills, able to influence both technical and non-technical stakeholders.
- Experience with AI and machine learning is a plus.