Fraud Risk Analytics Lead

2 weeks ago

Phoenix, Arizona, United States DataVisor Full time
Job Overview

DataVisor stands at the forefront of AI-driven Fraud and Risk Management solutions, providing unparalleled detection capabilities in the market. Our open SaaS platform facilitates seamless integration and enhancement of diverse data sources, enabling organizations to swiftly respond to evolving fraud and money laundering threats in real-time. Our proprietary unsupervised machine learning technology, combined with advanced device intelligence and robust decision-making tools, ensures immediate performance improvements from the outset. DataVisor's architecture is designed to accommodate various use cases across multiple business sectors, significantly reducing the total cost of ownership compared to traditional point solutions. We are proud to be recognized as an industry leader, serving numerous Fortune 500 companies worldwide.

Our award-winning platform is supported by a team of experts specializing in big data, machine learning, security, and scalable infrastructure. We foster a culture that is open, positive, collaborative, and focused on results.

Position Summary:

As a Fraud Analytics Manager, you will utilize our cutting-edge fraud detection SaaS offerings 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 clients in sectors such as FinTech, Banking, and E-commerce. Your expertise will encompass managing detection rules and evaluating model performance, while also providing strategic recommendations on risk management and operational practices. You will collaborate across teams, including Engineering, ML Modeling, and Product, to innovate and enhance our analytics solutions.

Key Responsibilities:

  • Analyze clients' risk scenarios and challenges, devising strategies to meet success criteria.
  • Develop and refine risk management strategies in partnership with clients.
  • Conduct risk pattern analyses, create executive dashboards, and monitor fraud detection effectiveness.
  • Facilitate technical discussions for in-depth fraud analyses to ensure the success of detection modules.
  • Collaborate with the ML modeling team to assess and improve detection quality through performance metrics.
  • Oversee the implementation of detection logic and rules to enhance fraud detection capabilities.
  • Serve as a technical liaison between clients and internal teams.
  • Regularly present key success metrics to both internal and external stakeholders.
  • This role may involve travel to strengthen client relationships through 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 fraud.
  • Strong data analytics skills with proficiency in SQL, Python, and R.
  • Experience in creating dashboards using tools like Tableau or Metabase.
  • Demonstrated ability to perform in-depth analyses of fraud patterns and decision-making strategies.
  • Exceptional communication and presentation skills.
  • Strong organizational skills and a sense of ownership over projects.
  • Experience in Banking/FinTech is advantageous.
  • Prior experience in fraud consulting is a plus.
  • Bachelor's degree in a technical or analytical field is required.

Benefits:

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

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