Sr. Data Analyst II, Fraud & Identity

Key Skills

Apache Hive, Dash framework, Data Analytics, Data Modeling, Data science techniques, Data Warehousing, ETL frameworks, Julia, Operations, Presto, Python Programming, R Programming, R-Shiny, Snowflake, SQL

Job Description

The Fraud & Identity Ops team at Instacart is a group of experienced and results-driven professionals passionate about driving profitable growth, generating cost savings, and accelerating the company's strategic priorities through Xfn partnerships with the Product, Engineering, Legal, and CX teams. Our team manages end-to-end strategy and operation for Fraud, Abuse, Identity, and Reconciliation. We value strategic thinking, creativity, and using data and insights to build consensus. This role reports to the Director of Fraud & Identity Operations, who manages loss from transaction and account risk. This senior analyst will work closely with other members of the Product, Engineering, Ops, and other cross-functional teams at Instacart.

About the Job

• Contributing to a high-performance culture delivering multiple projects, and priorities in a fast-paced and growing segment of Instacart business.
• Contributing to the development of the strategy for reporting, testing, analyzing, and forecasting business and risk performance for the Marketplace supporting Customers, Shoppers and Retailers. Also, own data analysis and visualization as it relates to all areas of Fraud, Abuse Identity, and Reconciliation
• Regularly communicate associated outcomes and insights to various stakeholders at all levels, including senior management to help guide strategic decisions for improvement
• Develop dashboards, analytical frameworks, and detailed reporting models that provide reliable, easily digestible insights to key stakeholders to help guide decisions around process, policy, systems, and service models
• Collaborate on roadmaps with the Product, Data Science, and other Analytics teams to understand the growth and risk factors of new and future product releases
• Develop a deep understanding of how each area of the business impacts the other, as well as the underlying correlations relating to key company metrics
• Create automated reporting to ensure operations leaders are informed of variations and opportunities across geographies and teams
• Analyze unstructured behavioral data to discover operational events and activities impacting fulfillment quality and customer, shopper, and retailer experience
• Fundamentally change the way our teams across North America think about exceptional performance and customer experiences through innovative, value-added data approaches and insights
• Regularly collaborate with other SMEs, and decision-makers to develop data-driven policies and models to improve overall fulfillment performance
• Designing and conducting A/B and multivariate tests by developing test plans, defining success metrics, analyzing, and transforming data into actionable insights

About You

Minimum Qualifications

• Minimum 8-10 years in analytics, business intelligence/operations, investment banking, or related environment
• Ability to Identify potential root causes contributing to potential change(s) in metrics and provide recommendations on mitigation strategy
• Ability to write complex and performant queries in your dialect of SQL to extract data from our data warehouse (Hive, Snowflake, or Presto experience a plus)
• Experience with R, Python, and/or Julia (fluency in at least one language preferred)
• Experience with analytical visualization tools such as Tableau, Looker, Periscope or similar tools
• 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, and 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
• Understanding of A/B testing and other forms of statistical analysis using statistical packages similar to R, SAS, or Pandas
• Experience in e-commerce, CNP payments, finance, SaaS, digital goods, or marketplace industry.
• Assess and measure the impact of product changes and vendor performance
• 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 payment processing, authentication, anti-fraud systems, and tools or vendors
• Experience in advanced reporting tools such as R Shiny, Dash, or Bokeh
• Advanced degree in statistics or other quantitative fields
• Experience with experimentation, Data modeling, ETL, and data pipeline development experience