Analyst, Fraud Strategy
About the position
As a Fraud Analyst, you will play a critical role in protecting the business from fraud losses while enabling sustainable growth. You will leverage data, analytics, and cross-functional collaboration to design fraud prevention strategies, build solutions, and deliver actionable insights that drive impact.
Responsibilities
• Assess fraud risks, evaluate controls, and identify gaps to help prioritize fraud mitigation projects.
• Develop and implement fraud detection rules using segmentation, predictive models, hypothesis testing, and other analytical methods.
• Investigate and analyze the latest fraud trends, designing proactive strategies to address them.
• Own and manage key processes to reduce fraud losses, including real-time monitoring, alerting, and performance tracking.
• Partner with stakeholders across Finance, Technology, Product, Marketing, Logistics, Legal, PR, Security, and other teams to leverage both company and third-party data.
• Design and execute A/B tests to measure the effectiveness of fraud prevention strategies.
• Conduct ad-hoc analyses, clearly communicate results, and present actionable insights to both senior management and technical/non-technical stakeholders.
• Independently manage small to medium-sized projects, while supporting larger initiatives with cross-functional collaboration.
Requirements
• Bachelor’s degree in a quantitative discipline (or equivalent work experience).
• 3–5 years of experience in fraud, risk, payments, analytics, or statistical roles.
• Prior exposure to statistics and machine learning modeling techniques through coursework or professional experience.
• Proficiency in SQL and experience with R or Python for data analysis and statistical modeling.
• Hands-on experience with data visualization tools such as Tableau or Excel.
• Experience automating reporting and building monitoring dashboards.
• Knowledge of fraud vectors, tools, strategies, and infrastructure in high-volume digital environments.
• Strong quantitative, analytical, and problem-solving skills with sharp attention to detail.
• High level of inquisitiveness, initiative, and critical thinking.
• Proven ability to translate analysis into implementable strategies and rules.
• Strong project management skills, including cost-benefit assessment, prioritization, documentation, and follow-through.
• Excellent communication skills, able to convey findings clearly to technical and non-technical stakeholders.
Nice-to-haves
• Experience in a digital marketplace or platform environment with high transaction volumes.
• Familiarity with advanced fraud detection systems, real-time monitoring frameworks, or machine learning approaches.
• Strong track record of effectively presenting insights to senior management and executive stakeholders.
Benefits
• Competitive salary package including equity and 401K.
• Multiple medical, dental, and vision plans.
• Many benefits and perks that are not listed.
As a Fraud Analyst, you will play a critical role in protecting the business from fraud losses while enabling sustainable growth. You will leverage data, analytics, and cross-functional collaboration to design fraud prevention strategies, build solutions, and deliver actionable insights that drive impact.
Responsibilities
• Assess fraud risks, evaluate controls, and identify gaps to help prioritize fraud mitigation projects.
• Develop and implement fraud detection rules using segmentation, predictive models, hypothesis testing, and other analytical methods.
• Investigate and analyze the latest fraud trends, designing proactive strategies to address them.
• Own and manage key processes to reduce fraud losses, including real-time monitoring, alerting, and performance tracking.
• Partner with stakeholders across Finance, Technology, Product, Marketing, Logistics, Legal, PR, Security, and other teams to leverage both company and third-party data.
• Design and execute A/B tests to measure the effectiveness of fraud prevention strategies.
• Conduct ad-hoc analyses, clearly communicate results, and present actionable insights to both senior management and technical/non-technical stakeholders.
• Independently manage small to medium-sized projects, while supporting larger initiatives with cross-functional collaboration.
Requirements
• Bachelor’s degree in a quantitative discipline (or equivalent work experience).
• 3–5 years of experience in fraud, risk, payments, analytics, or statistical roles.
• Prior exposure to statistics and machine learning modeling techniques through coursework or professional experience.
• Proficiency in SQL and experience with R or Python for data analysis and statistical modeling.
• Hands-on experience with data visualization tools such as Tableau or Excel.
• Experience automating reporting and building monitoring dashboards.
• Knowledge of fraud vectors, tools, strategies, and infrastructure in high-volume digital environments.
• Strong quantitative, analytical, and problem-solving skills with sharp attention to detail.
• High level of inquisitiveness, initiative, and critical thinking.
• Proven ability to translate analysis into implementable strategies and rules.
• Strong project management skills, including cost-benefit assessment, prioritization, documentation, and follow-through.
• Excellent communication skills, able to convey findings clearly to technical and non-technical stakeholders.
Nice-to-haves
• Experience in a digital marketplace or platform environment with high transaction volumes.
• Familiarity with advanced fraud detection systems, real-time monitoring frameworks, or machine learning approaches.
• Strong track record of effectively presenting insights to senior management and executive stakeholders.
Benefits
• Competitive salary package including equity and 401K.
• Multiple medical, dental, and vision plans.
• Many benefits and perks that are not listed.