Required Principal AI Scientist, Fintech Innovation Architecture
Job Overview
Join an amazing team driving cutting-edge AI solutions in the fintech industry, primarily focused on evaluating risk for lending products. This Principal role requires an exceptional blend of deep research, architectural mastery, and a powerful innovation mindset to pioneer new capabilities and deliver high-quality, end-to-end AI systems that shape the product direction for the next 510 years.
Responsibilities
System Architecture & Ownership
Own projects from conception to production, collaborating globally with partners to deliver complex projects.
Define the vision and direction for end-to-end solutions, serving as a thought leader on execution that brings immediate value and solves for the long-term vision.
Deliver robust, high-performance AI/ML system designs that meet critical requirements (latency, throughput, cost, maintenance).
Drive cross-functional end-to-end design architecture.
AI/ML Development & Leadership:
Lead the full cycle of big data exploration, including hypothesis formulation, advanced predictive statistical modeling, and algorithm development across complex, large-scale data.
Mentor existing Data Science teams, influence AI-driven product design and strategy with partner architects, and assist in the definition of roles and training needs.
Innovation & Research Strategy
Pioneer innovative Proof of Concepts (POCs) to show the way for where our Fintech products should go over the next 510 years, focusing on high-impact solutions like Explainable AI, Homomorphic Encryption, or advanced Behavioral Analytics.
Apply research to create high-impact solutions and represent the teams innovation to the wider organization.
Act as a Consultative Business Facilitator, exploiting revealed insights and providing entrepreneurial guidance for business stakeholders.
Requirements: Advanced degree (Statistics, Applied Mathematics, Computer Science, or related) or equivalent experience
Expert-level knowledge with modern AI development frameworks, and expertise in all steps spanning the end-to-end Model Development Life Cycle (MDLC)
Deep technical understanding of underlying Data Science concepts, going beyond just model training
Industry expert in ML, NLP, or Optimization
Expert knowledge in a range of statistical and machine learning techniques, including Supervised, Unsupervised, and Generative AI (autoencoders, GANs, VAEs)
5+ years of experience in developing predictive models in a financial services or risk management context is highly valued
Experience with ETL, data warehousing, cloud platforms, and Spark for ML feature creation
Strong communication and presentation skills to present complex insights to non-technical stakeholders
Large corporate experience and know-how, and demonstrable maturity are essential traits.
This position is open to all candidates.