Senior Business Data Analyst

Job Overview

Overview
Intuits Fraud Prevention team harnesses the power of data, technology, and people to protect our customers, partners, and business from fraud and abuse.
The Fraud Prevention team is looking for a Senior Business Data Analyst who is excited to partner with product managers, engineers, and data scientists to deliver fresh insights and solutions to fight fraud.
What you’ll bring
Strong business acumen and exceptional analytical ability with 3-5 years of relevant experience. Experience in Fraud Prevention or Risk preferred.
Advanced SQL and coding skills to perform data, profiling, segmentation and aggregation.
Experience with statistical analysis in support of justifying policy recommendations is preferred
Significant experience with relational databases (Oracle, SQL Server, MySQL, Vertica) preferred.
Good working experience with data analytics and visualization technologies (Excel, Python, Tableau, QlikView, etc.).
Outstanding communication skills with the ability to deftly negotiate, prioritize across technical and non-technical teams, influence decision makers and build consensus with teams.
Detail-oriented with a high degree of accountability, organization and empathy.
Experience working with Key Performance Indicator metrics such as conversion rates, user acquisition, retention, or product usage.
Bachelors Degree in Quantitative Field or commensurate experience. Masters degree preferred.

How you will lead
Translate business questions into verifiable hypotheses, create experiments to test them, and generate recommendations based on the findings
Leverage data to understand fraudulent behavior, identify trends that indicate elevated risk, and to inform policy decisions.
Proactively identify ways to improve existing processes and suggest projects that address key issues while providing an awesome and delightful customer experience.
Drive requirements for data engineers to design, test, and deliver accurate metrics related to fraud activity, policy rules, and operating effectiveness via dashboards using disparate data sources and systems.
Curate and standardize fraud-related datasets used as the foundation for all Intuit-wide fraud analysis
Use Excel or Google spreadsheets, Python, Tableau, and Splunk to quickly analyze, manipulate and visualize small to large datasets to guide fraud and risk policy discussions
Create clear concise diagrams to document key data and business processes
Vigorously test and validate the integrity and quality of data required for performing analysis
Partner with fraud investigation teams, policy makers, product managers, and data scientists to deliver data insights and analysis that inform critical decisions and help us reach our goals

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