Overview

About the Role - We are seeking a highly motivated, analytical, and organized individual to join the team who will leverage a combination of deep analytics skills and business acumen to identify, extract, and visualize opportunities across all areas of Fraud, which can then be used to drive meaningful improvements across various segments of the company. This role requires excellent time-management, effective communication skills for engaging with stakeholders at all levels, and a passion for continuous improvement, data integrity, and scalable solutions.

About the Team - The Fraud, Abuse,Identity & Reconciliation (F.A.I.R.) Ops & Analytics team at Instacart is a group of experienced, results-driven professionals dedicated to driving profitable growth, generating cost savings, and advancing the company's strategic objectives. By fostering strong cross-functional partnerships with Product, Engineering, Legal, and CX teams, we manage the end-to-end strategy and operations for Fraud, Abuse, Identity, and Reconciliation. We prioritize strategic thinking, creativity, and data-driven decision-making to build alignment and deliver impactful results.

This role reports to the Manager, Data Analyst, Fraud and Identity, who oversees Spread and Shopper costs along with financial losses related to Fraud, Abuse, Identity, and Reconciliations. The Senior Data Analyst will work closely with Product, Engineering, Operations, and other cross‑functional Analytics teams across Instacart.

About the Job 

This role focuses on utilizing data to uncover insights, develop strategies, and drive improvements across Payments, billing, and fraud processes—spanning everything from the user checkout experience to internal financial reporting.

• Ownership of Data Analysis & Visualization: Monitor and improve critical KPIs such as fraud costs, chargeback volume, fraud rates and revenue leakage.
• Strategic Communication: Regularly communicate outcomes and insights to cross-functional stakeholders, including senior leadership, to guide strategic decision-making for process and performance improvement.
• Development of Single Source of Truth (SSOT) Dashboards and Reporting Models: Work alongside DS & Broader Fraud & Identity analysts to implement robust models in DBT and Snowflake, and design dashboards that provide a unified view of business-critical Shopper fulfillment, Shopper Payment and PoS (point of sale) Checkout data. Work closely with Compliance and Legal teams to meet reporting requirements and successfully navigate audits
• Collaboration on Roadmaps: Work with Product, Data Science, and Xfn Analytics teams to understand growth and risk factors related to new and future fraud vectors.Operational Data Analysis: Analyze shopper behavioral signals to identify anomalous patterns indicative of fraud or policy abuse.
• A/B Testing & Experimentation: Design and conduct A/B and multivariate tests by developing test plans, defining success metrics, analyzing, and transforming data into actionable insights 
• Xfn Collaboration: Collaborate with the Engineering and Product team to instrument new product features and ensure great event tracking and data integrity.
• Automation and Reporting: Build automated reporting systems to keep operations leaders informed of trends, variations, and opportunities across geographies and teams. 

In this role, you’ll play a critical part in transforming how teams across North America leverage data to deliver exceptional performance and create industry-leading customer, shopper, and retailer experiences.

About You

Minimum Qualifications

• Minimum 6 - 8  years of analytical experience, preferably in payments,fraud or identity domains
• Ability to Identify potential root causes contributing to potential change(s) in metrics and provide recommendation on mitigation strategy 
• Strong analytical mindset with a track record of resolving complex transaction issues.
• High proficiency in SQL, with experience writing complex queries, joins, and optimizations.
• Experience with R/Python (fluency in at least one language preferred)
• Experience with analytical visualization tools such as Mode, Tableau, Looker, Periscope or similar tools
• Understanding of A/B testing and other forms of statistical analysis using statistical packages 
• Extremely strong verbal and written communication skills, including the ability to synthesize complex topics and create compelling narratives for various audiences
• Ability to work effectively with internal stakeholders, including data scientists and data engineers. Work cross functionally with Product, Engineering, Operations to drive changes
• Excellent teamwork skills and desire to help others learn
• High level of accountability and ownership – driven and focused self-starter
• Strategic mindset – the ability to think ahead of where the company is at now
• Experience in e-commerce, CNP payments, finance, SaaS, digital goods or marketplace industry.
• Experience in driving understanding of customers and their interaction with products, through in-depth analyses of user behavior and engagement

Preferred Qualifications

• Experience in Fraud, Reconciliation, Identity or Transaction Risk field
• Experience working with authentication, anti-fraud systems and checkout, tools or vendors
• Advanced degree in statistics or other quantitative fields
• Experience with experimentation, Data modeling, ETL and data pipeline development experience
• Proficiency with AI tools (e.g., Claude, ChatGPT, Copilot) and a demonstrated ability to integrate them into day-to-day workflows.

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