Data Analyst

2 weeks ago

Vancouver BC, Canada Instacart Full time

Data Analyst II 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. Additionally, the ideal candidate will possess excellent time-management skills, the ability to communicate & present information effectively to business partners at all levels, and a deep-seated passion for continuous improvement, data integrity, and scalable solutions.
About the Team 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.
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
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
Minimum 8-10 years in analytics, business intelligence/operations, investment banking, or related environment
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
Ability to work effectively with internal stakeholders, including data scientists and data engineers. Excellent teamwork skills and desire to help others learn
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
Experience in Fraud, Reconciliation, Identity, or Transaction Risk field
Experience working with payment processing, authentication, anti-fraud systems, and tools or vendors
Advanced degree in statistics or other quantitative fields
Experience with experimentation, Data modeling, ETL, and data pipeline development experience
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