Staff Fraud and Risk Analyst
Intuit
**Overview**
Intuit’s Trust and Safety team harnesses the power of data, technology, and people to protect our customers, partners, and business from fraud and abuse. The team is looking for a Staff Fraud Risk Analyst who is passionate about data and excited to partner with
product managers, engineers, and data scientists to deliver fresh insights and intelligent solutions to fight fraud. This individual will cultivate a deep understanding of our suite of Tax products and apply industry best practices around data security and fraud prevention to address large scale problems related to identity theft, account takeover, and product abuse, particularly in the tax preparation industry.
**What you'll bring**
+ Strong business acumen and exceptional analytical ability with 8+ 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 (Athena, Hive) preferred.
+ Significant experience with data analytics and visualization tools (Excel, GSheets, Python, Tableau, 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 using version control software like Git preferred but not required
+ Experience working with Key Performance Indicator metrics such as fraud prevention, chargeback, precision, recall, and customer insult rates (preferred).
+ Team player: Effectively drive decisions and delivery across organizational boundaries through collaboration and effective relationships
+ Bachelor’s Degree in Quantitative Field or commensurate experience. Master’s degree preferred.
**How you will lead**
+ Lead initiatives to understand fraudulent behavior, identify trends in the data that indicate elevated risk, and create policy recommendations/solutions.
+ Drive change by proactively identifying ways to improve existing processes and suggest projects that address key issues while providing an awesome customer experience.
+ 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.
+ Effectively design, document, and communicate complex analyses, data flows, and business processes
+ Design metrics and dashboards to effectively measure the impact of fraudulent activity and the policies designed to mitigate them
+ Advocate for the curation, standardization, and centralization of fraud-related datasets that form the foundation for all Intuit-wide fraud analysis
+ Be the subject matter expert across the organization for your fraud and risk domain
+ Use SQL, Python, Tableau, Databricks and spreadsheets to quickly analyze, manipulate and visualize datasets to guide fraud and risk policy discussions
+ Teach best practices and mentor analysts within the organization
_Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is:_
Mountain View-172,000 - 232,500
_This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at_ Intuit®: Careers | Benefits (https://www.intuit.com/careers/benefits/full-time-employees/) _).Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To dri_ _ve ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender._
EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.
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