Sr Staff AI Scientist, Fintech Innovation

Overview

Join an amazing team driving AI solutions in the fintech industry, primarily focused on evaluating risk for lending products. This Senior Staff role is a blend of leading the full AI/ML development cycle and acting as a Data Science Architect, responsible for all engineering aspects of the work to deliver excellent, high-quality, and operationally sound AI systems.

Responsibilities

System Architecture & Operational Excellence:

• Deliver robust AI/ML system designs that meet customer and systems requirements, including latency, throughput, cost, and maintenance.
• Working with partners and architects, define the vision and align on architecture for integration, ensuring excellent deliveries in terms of quality, stability, security, compliance, and operational excellence.
• Drive cross-functional end-to-end design architecture.
• Lead conversations with partner architects to influence AI-driven product design and strategy
  
  

• Lead the full cycle of iterative big data exploration, including hypothesis formulation, algorithm development, data cleansing, testing, and insight generation.
• Apply advanced, predictive statistical modeling and testing to extract data-driven insights from complex, large-scale data sources (relational and non-relational).
• Review complex and challenging work to help simplify and execute with speed.
  
  

• Provide guidance to business stakeholders on how best to harness available data and fully exploit the insights revealed through the research.
• Drive the design and creation of reusable AI capabilities.
  
  

• Advanced degree (Statistics, Applied Mathematics, Computer Science, or related), or equivalent experience
• 5+ years of experience in developing predictive models and statistical analysis in a financial services or risk management context
• Expert-level knowledge with modern AI development frameworks, and expertise in all the steps spanning the end-to-end MDLC.
• Strong proficiency in programming languages such as Python, R, or Scala, and expertise with Spark for data manipulation and ML feature creation
• Expert knowledge in a range of statistical and machine learning techniques, including Supervised, Unsupervised, and Generative AI (autoencoders, GANs, VAEs)
• Industry expert in ML, NLP or Optimization
• Practical experience with ETL processes, data warehousing, and cloud-based computing platforms
• Expert knowledge of data pipelines, processes, and design patterns, and ability to create logical and physical data models for cross-functional business problems
• Excellent communication skills, including the ability to present complex data and insights to non-technical business stakeholders