Title : Senior Data Analyst
Sunnyvale, CA Local
Key Responsibilities
• Analyze and optimize the end-to-end chargeback process by identifying root causes, trends, and opportunities for automation and cost reduction.
• Develop and maintain dashboards, reports, and analytical models to monitor chargeback performance, seller impact, and financial exposure.
• Collaborate cross-functionally with Product, Engineering, Risk, and Operations teams to design data-driven solutions that improve chargeback resolution efficiency and seller experience.
• Lead initiatives to enhance chargeback visibility and transparency for sellers, ensuring timely communication and actionable insights.
• Utilize advanced analytics and statistical techniques to inform chargeback policies, detect anomalies, and mitigate financial risk.
• Support the scaling of chargeback and settlement processes across global marketplaces by providing analytical insights and operational recommendations.
Success Criteria
• Strong analytical and problem-solving mindset with a bias for action.
• Ownership mentality with a focus on delivering measurable business outcomes.
• Deep empathy for partners and a commitment to improving their experience.
• Excellent collaboration and communication skills across technical and non-technical teams.
• Data-first decision-making approach with a strong storytelling ability.
• Trusted partner to cross-functional stakeholders.
• Values diverse perspectives and team collaboration.
• Results-oriented and self-motivated.
Qualifications
• Master’s degree in data science, Statistics, Computer Science, Economics, or a related field.
• 4+ years of industry experience in Payments, Risk, FinTech, or Marketplace Analytics.
• Proven ability to lead cross-functional initiatives and influence product and engineering roadmaps.
• Advanced proficiency in SQL, with experience working on cloud data platforms (e.g., BigQuery, Redshift, Snowflake).
• Strong experience with Python or R for data analysis, modeling, and automation.
• Proficiency in data visualization tools (e.g., Looker, Power BI, Tableau) and building self-serve analytics.
• Experience with A/B testing, experimentation frameworks, and causal inference techniques.
• Familiarity with real-time data systems, fraud detection models, and decisioning platforms is a plus.
• Excellent communication skills with the ability to translate complex data into actionable insights.
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