Vice President

Vice President – Fraud Strategy | Analytics | Banking & Financial Services

NYC, United States

Qualifications:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Business Analytics, or related field. Advanced degrees preferred.
• 12 years of experience in analytics, AI, or data science leadership roles, ideally within consulting or financial technology sectors.
• Experience in Fraud Analytics and Strategy:
• 8 years of experience in Fraud strategy (preferably Seller Risk Fraud)
• Experience with managing application fraud, transaction fraud
• Technical Skills Required: Familiarity with Hive, PySpark, SQL, Python, Machine Learning tools and Tableau / other data visualization techniques
• Familiarity with Fraud rule writing techniques and rule governance mechanisms.
• Ability to bring thought leadership to build real time Fraud solutions through analytics or internal tools.
• Proven track record managing large, strategic accounts with complex data and AI projects, preferably with experience working with leading banking or fintech clients.
• Deep expertise in AI/ML techniques, big data technologies, predictive analytics, and data engineering.
• Strong business acumen and ability to translate technical capabilities into strategic business value.
• Exceptional communication and stakeholder management skills, with experience engaging C-suite executives.
• Ability to travel as needed to client sites and industry events.

Key Responsibilities:

• Account Leadership: Lead and manage the client engagement, ensuring delivery of high-impact analytics and Fraud Analytics and Strategy projects aligned with strategic business priorities. Build and sustain strong executive-level relationships within the client.
• Team Leadership & Development: Manage and mentor a multidisciplinary team of data scientists, engineers, analysts, and consultants to foster innovation, technical excellence, and client satisfaction.
• Project Delivery & Quality Assurance:Oversee all phases of project lifecycle— from discovery and solution design to deployment and optimization— ensuring high-quality, scalable, and compliant AI solutions.
• Cross-functional Collaboration: Partner with sales, marketing, product, and technology teams to align analytics initiatives with broader business strategies.
• Thought Leadership & Industry Expertise: Represent at industry events, contribute to whitepapers, and share best practices on analytics and AI trends relevant to financial technology and payments.