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Fraud Risk Analytics Lead

2 months ago

Phoenix, Arizona, United States DataVisor Full time

Company Overview:

DataVisor stands at the forefront of AI-driven Fraud and Risk Management solutions, offering unparalleled detection capabilities in the market. Our open SaaS platform allows for seamless integration and enhancement of diverse data sources, empowering organizations to respond swiftly to evolving fraud and money laundering threats in real-time. With our innovative unsupervised machine learning technology, advanced device intelligence, and robust decision-making tools, we guarantee significant performance improvements from day one. Our platform is designed to cater to various use cases across multiple business units, significantly reducing the total cost of ownership compared to traditional solutions. Recognized as a leader in the industry, DataVisor has earned the trust of numerous Fortune 500 companies worldwide.

Position Summary:

As a Fraud Analytics Manager, you will leverage our cutting-edge fraud detection SaaS products to address the fraud and risk challenges faced by our key clients. You will deliver technical solutions and consultative services to a portfolio of Fortune 500 customers across the FinTech, Banking, and E-commerce sectors. Your expertise will encompass managing detection rules and model performance, providing strategic recommendations on risk management, and offering technical guidance through in-depth analysis and best practices on utilizing our Machine Learning models, Rules Engine, Device Intelligence Signals, and Case Manager.

Key Responsibilities:

  • Assess customer risk scenarios and challenges, developing actionable plans to meet success criteria.
  • Design, implement, and refine risk strategies in collaboration with clients.
  • Conduct risk pattern analyses, create executive dashboards, and monitor fraud detection performance.
  • Facilitate technical discussions for fraud investigations, ensuring the success of detection modules.
  • Collaborate with our ML modeling team to enhance detection quality through performance metrics evaluation.
  • Oversee the implementation of detection logic and rules to improve detection efficacy.
  • Act as a technical liaison between clients and internal teams.
  • Regularly present key success metrics to both internal and external stakeholders.
  • Travel may be required to strengthen client relationships through onsite workshops and business reviews.

Qualifications:

  • Minimum of 2 years of experience in fraud/risk management and analytics within banking, fintech, or payment sectors, utilizing machine learning models and rules to combat various forms of fraud.
  • Strong data analytics skills with proficiency in SQL, Python, and R.
  • Experience in developing dashboards using tools like Tableau or Metabase.
  • Demonstrated success in conducting deep dive analyses on fraud patterns and decision-making strategies.
  • Exceptional communication and presentation abilities.
  • Strong organizational skills and a sense of ownership over projects.
  • Prior experience in Banking/FinTech is advantageous.
  • Consulting experience in fraud management is a plus.
  • Bachelor's degree in a technical or analytical field.

Benefits:

Competitive bonus structure, comprehensive health insurance, and additional benefits.