Business Data Analytics, Payments Fraud

Business Analytics Lead Analyst — Fraud Strategy & Intelligence About Blend
360

Blend
360 is a premier AI and analytics services company that helps organizations solve their most complex data and technology challenges. We partner with leading enterprises across financial services, healthcare, retail, and other industries to deliver high-impact analytics, machine learning, and data engineering solutions. Our team of experts embeds directly with client organizations to drive measurable business outcomes from fraud prevention and risk management to customer intelligence and operational optimization.

At Blend
360, we don't just build models and dashboards, we build partnerships. We bring deep domain expertise, cutting-edge technical capabilities, and a collaborative approach to every engagement, ensuring our clients stay ahead in an increasingly data-driven world.

As a Business Analytics Lead Analyst on our Fraud Analytics, Modeling & Intelligence team, you will manage and execute fraud analytics and strategies supporting Blend
360's financial services clients across North America and globally. This includes leveraging data to identify fraud trends and designing and implementing strategies to prevent and mitigate fraud attacks across the full fraud lifecycle, including application and synthetic , account takeover, and sophisticated new attack schemes.

You will partner closely with client Fraud Policy, Operations, and cross-functional teams to stay apprised of business and technology direction and determine potential and existing fraud impacts.

The ideal candidate should have a solid foundation in Fraud Analytics, with demonstrated experience in one or more of the following areas:

• Fraud Strategy Analytics — Building and evaluating fraud detection rules and strategies
• Fraud Modeling — Developing and validating fraud risk models
• Fraud Project Management — Leading or contributing to fraud-related initiatives and programs within a financial services environment

• Support implementation of fraud risk strategies for consumer, small business, and commercial credit products with decision engine systems in accordance with defined change control procedures and controls.
• Assist in the management of business requirements, testing, and implementation of projects impacting fraud decision systems as well as system incidents.
• Refine framework for change control risk assessment including evaluation of control gaps within existing processes.
• Support Authorization Governance processes, evaluating historical performance and emerging changes in the environment.
• Build effective relationships within and outside the Fraud organization to help ensure successful and timely execution of key portfolio priorities.
• Generate and manage regular and ad-hoc reporting to enable effective monitoring and identification of emerging trends.
• Recommend actions for future development and strategic business opportunities, as well as enhancements to operational policies.
• Identify data patterns and trends, and provide insights to enhance business decision-making capability in business planning, process improvement, and solution assessment.
• Translate data into consumer and customer behavioral insights to drive targeting and segmentation strategies, and communicate clearly and effectively to business partners and senior leaders.
• Maintain familiarity with model development, monitoring, and versioning in production environments.
• Serve as a key partner managing Fraud Model Risk, including stakeholder interaction with model developers, vendors, and Model Risk Management validators across the model lifecycle — including validation, ongoing performance evaluation, and annual reviews.
• Conduct analysis and package it into detailed technical documentation reports for validation purposes sufficient to meet regulatory guidelines and exceed industry standards.
• Present model validation findings to senior management, supervisory authorities, and regulatory agencies as required.
• Continuously improve processes and strategies by exploring and evaluating new data sources, tools, and capabilities.
• Work closely with internal and external business…