| Job Description: |
Top 3 Required Skills:
1.Fraud investigation and mitigation
2.Splunk experience
3.AWS and Machine Learning and SQL queries
Top 3 Preferred Skills:
1.Python scripting
2.Setting up Dashboards and Alerts
3.Machine Learning, ETL
We are looking for a Splunk expert with advanced data engineering and analytical skills to join our Fraud and Cyber Risk team. This role is pivotal in leveraging Splunk’s full capabilities to uncover fraud and cybersecurity vulnerabilities, identify patterns and typologies, and provide actionable insights that strengthen our defenses.
Key Responsibilities
Splunk Mastery
Develop and optimize complex Splunk queries, dashboards, and alerts to extract actionable intelligence from large, diverse datasets.
Deeply understand and interpret Splunk metadata to surface hidden signals that indicate fraud or cyber threats.
Engineer Splunk-based solutions for proactive monitoring and anomaly detection.
Data Engineering & Integration
Design innovative data flows using non-traditional methods, integrating Splunk data with Excel and other sources.
Build scalable ETL processes to support fraud and cyber risk analytics.
Fraud & Cyber Intelligence
Analyze data to identify emerging fraud typologies, attack patterns, and systemic vulnerabilities.
Provide insights and recommendations for controls, fixes, and mitigation strategies.
Collaborate with fraud, cyber, and risk teams to operationalize intelligence findings.
Continuous Innovation
Stay ahead of evolving fraud and cyber threats, Splunk advancements, and data engineering best practices.
Drive new approaches for leveraging Splunk and metadata to enhance detection and prevention frameworks.
Qualifications
Technical Expertise:
Advanced Splunk skills (querying, dashboards, alerting, metadata analysis) – must be expert level.
Strong understanding of Splunk architecture and data ingestion processes.
Experience integrating Splunk with other data sources (Excel, APIs, etc.)
Analytical Skills:
Ability to detect patterns, anomalies, and typologies in large datasets.
Strong problem-solving mindset focused on fraud and cyber risk mitigation.
Preferred Experience:
Background in fraud analytics, cybersecurity, or risk management.
Familiarity with scripting languages (Python, SQL) for advanced data manipulation.
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