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Risk Analyst E-Commerce
2 weeks ago
Job Title: Risk Analyst Commerce
About the Role:
We are seeking a skilled and detail-oriented Risk Analyst to join our Commerce Risk team. This role is critical in driving risk intelligence through data-backed insights and timely analysis. The ideal candidate will not only work with large datasets and analytical models but will also be responsible for translating technical findings into clear, actionable summaries for leadership and cross-functional stakeholders.
The analyst is expected to identify risks, uncover patterns in user behavior, and support strategic risk mitigation decisions across the platform, particularly in the areas of customer abuse, promotional misuse, and trust violations.
Key Responsibilities:
- Prepare and analyze complex datasets to identify risk patterns, surface anomalies, and validate business hypotheses.
- Build concise summaries and visualizations that simplify technical data for diverse audiences, enabling informed decision-making across Risk, Product, and Business teams.
- Communicate insights through clear narratives, providing actionable recommendations and highlighting associated risks and trade-offs.
- Design and execute BI and reporting frameworks to monitor key metrics, rule performance, and customer impact across commerce brands.
- Collaborate with data engineering teams to maintain robust data pipelines and models for risk signal generation.
- Contribute to data modeling efforts and manage risk-centric data structures within the data warehouse.
- Support development and refinement of risk rules and machine learning models to strengthen detection of fraudulent or abusive behaviors.
- Maintain documentation and continuously evolve analysis SOPs based on the latest business rules, thresholds, and ecosystem learnings.
Role Requirements:
- 3-5 years of hands-on experience in risk analytics, fraud detection, or business intelligence, preferably within eCommerce or fintech domains.
- Proficient in SQL and Python for data extraction, transformation, and visualization; exposure to tools like R, Tableau, Power BI is a plus.
- Strong understanding of data warehousing, data modeling, and performance monitoring techniques.
- Experience working with rule-based and predictive risk frameworks is preferred.
- Excellent communication and storytelling skills, with the ability to present insights to non- technical audiences in a structured and impactful manner.
- Proven experience working in cross-functional environments, balancing business priorities and analytical rigor.
Basic Qualifications:
- Bachelors degree in a quantitative discipline such as Statistics, Mathematics, Economics, Computer Science, or a related field.
