Credit Fraud Analytics Director

About Yodlee

At Yodlee Inc, we’re at the forefront of innovation, utilizing cutting‑edge Machine Learning algorithms and Big Data Engineering frameworks. Our high‑caliber, mission‑driven culture empowers teams to tackle challenging and rewarding projects that drive impactful business decisions across the global financial services landscape.

• The Credit & Fraud Analytics Director is responsible for leading the development and management of risk analytics products and services, with a special focus on data‑driven financial decisioning in credit and fraud risk management. This role involves data analysis, strategic planning, product innovation, market analysis and hands‑on product development to enhance the organization’s analytics offerings.

• Lead credit and fraud risk analytics with deep expertise in financial‑services data science.
• Shape strategy, roadmaps, and product vision for data‑driven credit and risk solutions.
• Champion products to influence leadership alignment and prioritization.
• Demonstrate new capabilities through pilots, POCs, and ad‑hoc implementations.
• Define product design elements including features, pricing, and partnership models.
• Collaborate with technology teams to integrate off‑the‑shelf and custom solutions.
• Establish processes, ensure quality compliance, and guide teams in structured problem‑solving.
• Provide technical and functional leadership to solve complex business and engineering challenges.
• Support hiring, coaching, and performance feedback while ensuring adherence to legal and compliance requirements.
• Partner with go‑to‑market teams and internal SMEs to maximize product value and client impact.

• 5+ years of experience mentoring analytics team members and in analytics application/solution development. This refers to the implementation of repeatable analytic solutions which encompass all phases of the software development cycle, beyond model development.
• Strong experience developing analytical products or decision‑support solutions within credit, fraud, or financial services domains, with demonstrated understanding of regulatory considerations and risk management frameworks.
• Hands‑on data analytics experience, including exploratory data analysis, feature engineering, and translating large, complex datasets into deployable solutions that drive measurable business outcomes.
• 8+ years of professional experience and a Master of Arts/ Science or equivalent degree in computer science or related area of study
• 4+ years use of R, SQL for data mining and analysis.
• Strong programming skills in Python and familiarity with statistical and ML frameworks
• Proven ability to collaborate across diverse functional areas, bridging technical and business stakeholders. Must excel at connecting business requirements to data mining objectives and to measurable business benefit.