The Data Insights & Analytics Engineer transforms the Unified Commerce Platform’s (UCP) extensive commerce data into actionable intelligence that drives strategic decision-making across the organization and for our external partners. This role goes beyond standard reporting to uncover critical patterns in payment behaviors, fraud indicators, revenue optimization opportunities, and customer engagement. The ideal candidate will develop compelling data narratives that illuminate business performance, identify emerging risks, optimize marketing effectiveness, and enhance the overall commerce ecosystem for our diverse tenant base.
What you'll be doing:
Design and develop comprehensive analytics solutions and interactive dashboards for subscription metrics, payment performance, fraud patterns, and revenue optimization
Build robust reporting frameworks with scalable solutions and customizable templates for internal and external stakeholders
Develop payment analytics, fraud detection models, chargeback analysis frameworks, and revenue leakage detection systems
Transform complex data into compelling narratives through executive-level presentations and self-service documentation
Create attribution analytics, customer segmentation models, and lifecycle analytics to optimize marketing investments
Collaborate with cross-functional stakeholders to translate business questions into technical analytics requirements
Research and implement advanced analytics techniques while staying current with industry trends
Establish data validation frameworks and monitoring systems to ensure the accuracy of financial and behavioral metrics
What we want to see:
Bachelor's degree in Data Science, Statistics, Business Analytics, or related field
5+ years of experience in data analytics with exposure to commerce, payments, or subscription businesses
Proficiency with Apache Spark and Databricks for large-scale data transformation, analysis, and developing production-ready notebook workflows
Strong proficiency in SQL and data analysis programming languages (Python, R)
Experience with business intelligence and visualization tools (AWS Quicksight, Tableau, Power BI, Looker)
Knowledge of financial metrics, payment KPIs, and risk indicators
Experience translating complex transactional data into business insights
Background in developing dashboards for different audiences with varying technical sophistication
Understanding of fraud analytics, payment performance metrics, or revenue optimization techniques
Ways to stand out from the crowd:
Master's degree in a relevant field
Experience with commerce platforms, payment processors, or fraud prevention systems
Background in marketing analytics, customer segmentation, or lifetime value modeling
Knowledge of machine learning techniques for anomaly detection or predictive analytics
Experience with financial reporting, revenue forecasting, or business performance analysis
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