Fraud Ops and Automation Engineer

Job Description

This job posting has expired and no longer accepting applications.

We seek a highly motivated and detail-oriented Operations and Fraud Analyst to join our dynamic team. This role offers a unique opportunity to blend operational excellence with data-driven insights. You will be critical in ensuring smooth user support operations, mitigating fraud risk, and contributing to a data-informed environment. If you are passionate about automation and keen to develop your data analysis skills, this is the perfect role for you.

Key Responsibilities:

User Support:

Zendesk Mastery and GDPR Compliance: Manage our Zendesk system and optimize workflows and automated responses to enhance efficiency and maintain high levels of customer satisfaction.

Team Leadership and Quality Assurance: Conduct monthly performance reviews, analyze ticket volume and trends, and ensure adherence to SLAs, and quality guidelines.

Stakeholder Collaboration: Manage escalated tickets and collaborate effectively with Marketing, Demand and Supply Account Managers, and PR to resolve critical issues, including those impacting brand reputation.

Fraud Prevention:

Data-Driven Investigations:Analyze advertiser fraud claims , identifying patterns and trends to mitigate financial risk using python or SQL using cloud based data intelligence platform such as Databricks.

Investigate complex cases and connect with key stakeholders to strengthen fraud prevention efforts.

Financial Reconciliation: Maintain accurate records of fraud-related chargebacks with the Accounting team.

Performance Tracking and Reporting: Manage and track open fraud cases in Jira, ensuring adherence to SLAs and providing key insights to the Business team.

Your Profile:

Operational Excellence: Proven experience in a customer support or operations role, with a strong focus on efficiency and process improvement.

Data Analysis Foundations: Demonstrated ability to use SQL for data extraction and analysis. Experience with data visualization tools like Tableau or Excel is a plus.

Eagerness to Learn: A strong interest in developing data analysis skills and contributing to data-driven decision-making.

Excellent Communication: Strong written and verbal communication skills, with the ability to collaborate effectively with diverse stakeholders.

Problem-Solving Mindset: A proactive and analytical approach to problem-solving, with the ability to identify and address issues effectively.

Bonus Points: Experience with AWS or GCP or Databricks database management is highly advantageous.

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