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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, providing unparalleled detection capabilities in the market. Our open SaaS platform allows for seamless integration and enhancement of diverse data, enabling organizations to respond swiftly to evolving fraud and money laundering threats in real-time. Our patented unsupervised machine learning technology, coupled with advanced device intelligence and a robust decision engine, ensures immediate performance improvements from day one. DataVisor's platform is designed to accommodate various use cases across multiple business units, significantly reducing total ownership costs compared to traditional solutions. We are proud to be recognized as an industry leader, trusted by numerous Fortune 500 companies worldwide.

Team Culture:

Our award-winning software is developed 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 achieving results.

Position Summary:

As a Fraud Risk Analytics Lead, you will utilize 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 clients in sectors such as FinTech, Banking, and E-commerce. Your expertise will encompass managing detection rules and analyzing model performance, as well as providing strategic recommendations on risk management and operational processes. You will collaborate across departments, including Engineering, ML Modeling, and Product teams, to innovate and enhance our analytics solutions.

Key Responsibilities:

  • Analyze customer risk scenarios and challenges, developing tailored plans to meet success criteria.
  • Design, implement, and refine risk management strategies in partnership with clients.
  • Conduct risk pattern analyses, create executive dashboards, and monitor fraud detection efficacy.
  • Facilitate technical discussions for in-depth fraud investigations, ensuring 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 boost detection effectiveness.
  • Serve as a technical liaison between clients and internal teams.
  • Regularly present key success metrics to both internal and external stakeholders.
  • Occasional travel may be required to strengthen client relationships and conduct workshops.

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 capabilities using tools such as SQL, Python, or R.
  • Experience in developing dashboards with Tableau or Metabase.
  • Proven success in conducting in-depth analyses of fraud patterns and decision-making strategies.
  • Exceptional communication and presentation skills.
  • Effective time management and project ownership abilities.
  • Prior experience in Banking/FinTech is advantageous.
  • Experience in fraud consulting is a plus.
  • Bachelor's degree in a technical or analytical field.

Benefits:

We offer a competitive bonus structure, comprehensive health insurance, and additional benefits.