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Staff Data Analyst, Risk & Fraud

Category Security, Risk & Fraud Location Petach Tikva, Israel Job ID 18444
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Company Overview

Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Job Overview

As a Staff Analyst on the Trust and Safety Analytics team, you will be responsible for identifying, making available, and leveraging critical data elements to optimize Intuit’s ability to fight fraud, protect its customers and enforce acceptable use of products and services. Specifically, you will focus on applying your analytical skills to design, support and scale tools, processes, and strategies that proactively identify and mitigate risks across the organization.


Responsibilities

  • Collaborate closely with Engineering and Product teams to design, implement, and maintain analytics frameworks, tools, and data systems that support effective data monitoring and risk management strategies, enabling informed, data-driven decision-making.

  • Take an active role in the analytics team's efforts to manage and enhance Trust and Safety platform capabilities. Provide timely insights and actionable recommendations to strengthen platform performance and address emerging challenges. Develop tools and systems to measure platform health and assess risks, including designing dashboards to track performance metrics, analyze trends, and identify areas that require attention or intervention.

  • Ensure analytics systems are consistently reliable, accurate, and available. Establish proactive monitoring processes and implement thorough testing to detect and address issues, minimizing system disruptions or delays.

  • Contribute to effective incident management by using analytics to identify root causes, provide actionable insights, and continuously improve platform risk mitigation solutions.

  • Stay abreast of the latest developments in AI, and integrate insights into your analysis to address emerging risks   


Qualifications


  • Minimum 5 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, capable of thinking beyond immediate tasks to the broader goals of trust and safety

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). 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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