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Staff Fraud Analyst - TurboTax Fraud
- Intuit (Mountain View, CA)
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Overview
Intuit is a global platform company that is on a mission to power prosperity around the world for
consumers, small businesses and the self-employed. Across our four leading brands – Turbo Tax,
Credit Karma, QuickBooks, and Mailchimp – Intuit serves over 100M customers and is one of the few
companies in the world to have both a thriving consumer and small business ecosystem. Intuit is
known for its in
We are seeking a Fraud Analyst to join our Trust & Safety team.
In this role, you will play a crucial part in safeguarding our products from fraudulent activities. Your
primary responsibility will be to analyze data to uncover patterns of fraud, aiming to gain a
comprehensive understanding of how bad actors operate. This requires a keen eye for detail, strong
analytical skills, and familiarity with data visualization techniques. You will be responsible for creating
intuitive dashboards that will allow your stakeholders to monitor and mitigate these fraudulent patterns
efficiently.
You
•ll be a good fit to this role if you are:
+ A problem solver with strong analytical skills.
+ A creative and critical thinker.
+ Unafraid to question fundamental assumptions.
+ Naturally inquisitive and always looking to expand your knowledge.
+ Capable of working independently and making decisions with little direction.
+ Capable of communicating ideas clearly and concisely.
Responsibilities
+ Transform data into actionable and relevant insights for your stakeholders.
+ Formulate well-defined requirements for data engineering teams, ensuring that stakeholders have access to lucid, accurate, and consistent datasets.
+ Build and maintain dashboards to assess the efficacy of our controls in mitigating fraud, while ensuring minimal impact on our customers.
+ Equip fraud policy teams with a comprehensive understanding of the ecosystem, enabling them to recognize opportunities for improvement and optimization of their solutions.
+ Perform in-depth exploration and analysis of both internal and external data sources.
+ Identify developing patterns of fraudulent activities within Intuit's extensive range of products.
+ Communicate regularly with leadership, peers, and stakeholders, highlighting achievable goals and measurable business outcomes.
+ Work closely with local and global teams in policy, product, data engineering, data science and R&D.
Qualifications
Required Qualifications:
+ +6 years of experience analyzing complex datasets, and providing business
+ recommendations.
+ +4 years of experience working in an e-commerce, payments, or financial services
+ company.
+ +4 years of experience building dashboards and data visualization.
+ Extensive SQL experience, specifically in your current role.
+ Proven ability to work independently and make decisions with minimal direction within
+ assigned timelines.
+ Able to express thoughts and ideas in fluent and concise manner.
Preferred Qualifications:
+ Background in fraud prevention, with emphasis on tax fraud.
+ Bachelor’s degree, or foreign equivalent, in computer science, information systems
+ management, engineering (any field), or closely related quantitative discipline.
+ Experience building ETL pipelines.
+ Experience with Tableau/QlikView or and other data visualization software.
+ Experience with Github / Splunk / Python
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. 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 drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:
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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