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As a Senior Analyst on the Trust and Safety Analytics team, you will play a critical role in identifying, analyzing, and operationalizing key data signals to help Intuit prevent fraud, protect customers, and enforce acceptable use of products and services. You will apply strong analytical and technical skills to support and scale risk detection tools, monitoring processes, and mitigation strategies across Trust & Safety. This role partners closely with Product, Engineering, and Operations teams to deliver insights that drive data-informed decisions and measurable risk reduction.
Responsibilities
Partner with Engineering and Product teams to support the design, implementation, and maintenance of analytics tools, dashboards, and data pipelines that enable effective fraud and risk monitoring.
Analyze large, complex datasets to identify trends, anomalies, and emerging fraud patterns, translating findings into actionable recommendations.
Contribute to the ongoing improvement of Trust & Safety platforms, including monitoring performance metrics, assessing platform health, and identifying risk gaps or degradation.
Design and maintain dashboards and reporting (e.g., Tableau) to track fraud performance, operational efficiency, and risk exposure.
Ensure data quality and reliability by performing validation, testing, and monitoring of analytics outputs; proactively identify and escalate issues.
Support incident analysis and investigations by using data to identify root causes, quantify impact, and recommend mitigation actions.
Stay current on fraud trends, AI-driven abuse, and industry best practices, incorporating new insights into analyses and detection strategies.
Clearly communicate insights to both technical and non-technical stakeholders, influencing decisions through data-backed storytelling.
Qualifications
Minimum 4 years of experience in analytics, risk management, or security roles within the fintech, eCommerce, technology, or cybersecurity industries
Experience with anomaly detection, predictive modeling, or fraud risk strategies
A solid understanding of fraud prevention, and AI-driven risks in the current industry landscape
Strong proficiency in Python/SQL for data querying, analysis, and visualization
Hands-on experience with Business Intelligence tools like Tableau
Familiarity or prior experience with Generative AI models is a strong plus
An educational background in Mathematics, Statistics, Computer Science, or equivalent field (Bachelor’s degree required).
Demonstrated ability to deliver impactful analytics and insights in complex, fast-paced environments
Experience in analyzing large datasets, identifying trends, and drawing actionable conclusions
Comfortable working independently while collaborating effectively across internal teams to drive alignment and solutions
Strong communication skills, with the ability to articulate complex findings to technical and non-technical stakeholders alike
Attention to detail and a strategic mindset
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may 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). 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.
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About Intuit
Reviews
3.6
9 reviews
Work Life Balance
3.8
Compensation
3.2
Culture
3.1
Career
3.7
Management
3.0
65%
Recommend to a Friend
Pros
Flexible schedule and work independence
Good benefits and 401k match
Supportive teammates and collaboration
Cons
Management issues and favoritism
High pressure and quotas
Poor communication and politics
Salary Ranges
91 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Business Data Analyst
2 reports
$134,007
total / year
Base
$116,528
Stock
-
Bonus
-
$123,571
$134,007
Interview Experience
7 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
14%
Experience
Positive 14%
Neutral 86%
Negative 0%
Interview Process
1
Application Review
2
Online Assessment/Technical Screen
3
Live Coding Interview
4
Case Study/Technical Assessment
5
Behavioral Interview
6
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Case Study
System Design
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