Business Intelligence Engineer, ISFX

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Skills you'll use

What you'll do

• ● Design and build MCP server as a centralized knowledge repository, exposing lead context, seller signals, program rules, and historical outcomes to AI agents and tools across Amazon MCP compliant platforms
• ● Develop and maintain ML driven scoring and prioritization models (intent scoring, conversion prediction, multi signal ensemble models) working alongside the shared Data Scientist, with ownership of feature engineering, model evaluation, and production deployment
• ● Create, support and continuously improve reports and metrics that support the business operations
• ● Design and implement data pipelines (SQL, Python, Airflow) that process seller signals, engagement data, and pipeline metrics into actionable intelligence
• ● Drive automation of repetitive reporting and assignment tasks to scale intelligence delivery across regions
• ● Convert data into digestible business intelligence and actionable information using tools like QuickSight/Tableau
• ● Shape and deliver key metrics, reports, and indicators by which our business will assess its performance
• ● Dive deep into large data sets to answer specific business questions using Excel, SQL and other data manipulation languages
• ● Work directly with business teams to utilize metrics and analysis to determine improvement opportunities
• ● Identify process improvement opportunities and drive automation to scale reporting solutions

Who can apply

• - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
• - 2+ years of Tableau Desktop, Quicksight or other relevant data visualization software experience
• - Bachelor's degree or above in business administration, finance, economics, computer science, data science, engineering, or other related field, or 2+ years of Amazon RME (BB/3P) Full Time Exempt experience
• - Experience with data visualization using Tableau, Quicksight, or similar tools
• - Experience with data modeling, warehousing and building ETL pipelines
• - Experience in Statistical Analysis packages such as R, SAS and Matlab
• - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
• - Experience using SQL (Structured Query Language) to pull data from a database or data warehouse
• - Experience using Python scripting to process data for modeling
• - Proficiency in Python for data manipulation, automation, and ML model development

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