Required Sr Staff AI Scientist, Fintech Innovation
Job 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
AI/ML Development & Modeling:
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.
Strategy & Consultation:
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.
Requirements: 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.
This position is open to all candidates.