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.

About The Role

• 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.
  
  

What You'll Do

• 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.
  
  

Qualifications

• 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.