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Risk and Compliance Analyst *** Direct end client ***

Projas Technologies, LLCMountain View, CA🇺🇸United StatesPosted 31 Aug 2026

Why This Role Stands Out

This hybrid role offers a fantastic opportunity to develop your skills in fraud prevention and data analytics, directly impacting customer trust and business outcomes within a reputable tech company. You'll thrive here if you possess strong analytical abilities and a passion for leveraging data and AI to combat complex fraud challenges, so we encourage you to apply.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Mountain View, CA, United States
Posted
Yesterday
SQLETLMachine LearningTableauBusiness AnalysisComplianceDatabricksHiveProcess ImprovementPythonRisk AssessmentRisk ManagementRoot Cause AnalysisStakeholder ManagementStrategic Planning

Job Description

We are seeking a highly analytical and data-driven Risk and Compliance Analyst to help combat fraud across digital consumer platforms. This role will partner closely with Product Managers, Engineers, Data Scientists, and Fraud Operations teams to identify fraud patterns, develop risk strategies, and drive data-informed decisions that improve customer trust and business outcomes.

The ideal candidate has strong experience in fraud prevention, risk analytics, data analysis, and policy development, with expertise in leveraging data, AI-driven solutions, and advanced analytics to detect and mitigate fraudulent activity such as identity theft, account takeover, and product abuse.

Key Responsibilities

  • Lead fraud risk initiatives by analyzing customer behavior, transaction trends, and emerging fraud patterns.
  • Identify high-risk activities and develop actionable policy recommendations to reduce fraud exposure.
  • Drive process improvements and recommend strategic projects that enhance fraud prevention while maintaining a positive customer experience.
  • Utilize AI and advanced analytics techniques to optimize fraud detection and prevention capabilities.
  • Collaborate with Fraud Operations, Product, Engineering, Data Science, and business stakeholders to deliver actionable insights and support critical decision-making.
  • Design, build, and maintain fraud-related metrics, dashboards, and reporting solutions.
  • Document and communicate complex analyses, workflows, data processes, and business recommendations to technical and non-technical audiences.
  • Support the development, standardization, and governance of fraud-related datasets and analytical frameworks.
  • Serve as a subject matter expert in fraud risk management and fraud analytics.
  • Analyze, manipulate, and visualize large datasets using SQL, Python, Tableau, Databricks, spreadsheets, and related analytical tools.
  • Mentor junior analysts and promote analytical best practices throughout the organization.

Required Qualifications

  • Bachelor's degree in a quantitative discipline such as Statistics, Mathematics, Economics, Computer Science, Data Analytics, Engineering, or equivalent practical experience.
  • 4+ years of experience in data analytics, fraud risk, risk management, or a related analytical field.
  • Advanced SQL skills with strong experience in data profiling, segmentation, aggregation, and analysis.
  • Proficiency in Python and data analytics methodologies.
  • Experience working with data visualization and reporting tools such as Tableau, Excel, and Google Sheets.
  • Strong analytical and problem-solving abilities with excellent business acumen.
  • Excellent communication and stakeholder management skills, with the ability to influence decisions across technical and non-technical teams.
  • Strong organizational skills, attention to detail, and accountability.
  • Proven ability to work effectively in cross-functional environments.

Preferred Qualifications

  • Experience in Fraud Prevention, Fraud Risk Management, Trust & Safety, or Financial Risk.
  • Knowledge of statistical analysis techniques and experimentation methods.
  • Experience with Hive, Databricks, or large-scale distributed data environments.
  • Familiarity with fraud detection models and risk scoring methodologies.
  • Experience tracking and optimizing key fraud metrics such as:
    • Fraud Prevention Rate
    • Chargeback Rate
    • Precision
    • Recall
    • Customer Impact Metrics
  • Master's degree in a quantitative field.

SQL, Python, Tableau, Databricks, Hive, Excel, Google Sheets, Data Analytics, Data Visualization, Statistical Analysis, Relational Databases, Data Profiling, Data Segmentation, Data Aggregation, Dashboard Development, Reporting, Risk Analytics, Fraud Analytics, AI Tools, Machine Learning, Big Data, Data Mining, Data Modeling, ETL, KPI Reporting, Business Intelligence

Fraud Prevention, Fraud Risk Management, Risk Analysis, Identity Theft Detection, Account Takeover Prevention, Product Abuse Detection, Trust and Safety, Fraud Investigation, Policy Development, Risk Assessment, Fraud Monitoring, Data-Driven Decision Making, Process Improvement, Customer Experience, Stakeholder Management, Cross-Functional Collaboration, Business Analysis, Root Cause Analysis, Trend Analysis, Risk Mitigation, Fraud Detection Strategies, Subject Matter Expert, Mentoring, Leadership, Analytical Thinking, Problem Solving, Performance Metrics, Chargeback Analysis, Precision and Recall, Operational Excellence, Strategic Planning, Fraud Operations, Consumer Products Risk Management, Decision Support, Business Acumen, Communication Skills

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