Director, Data Science - Customer Core Specialist Models

Capital One-posted 3 months ago
$263,900 - $328,500/Yr
Full-time • Senior
San Jose, CA
Credit Intermediation and Related Activities
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Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As an Data Scientist Leader at Capital One, you'll be part of a team that's leading the next wave of AI-driven disruption at a whole new scale, using the latest in computing and AI/ML technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description: The Specialist Models Team in AI Foundations engages in active research in GenAI and AI powered capabilities to build scalable futuristic solutions to enhance our customers digital experience and provide them with superior protection in their financial lives. You will be the driving force to lead research, innovate and develop applications with emerging AI/ML technologies. Our areas of research include advanced LLM powered search, natural language interfaces, advanced biometrics, recommendation and personalization systems, Highly Sensitive Human Data detection systems, Guardrails, and Red-teaming to build safe and reliable AI systems.

  • Lead a cross-functional team of data scientists, software engineers, machine learning engineers and work with product managers and Engineers to deliver AI powered products.
  • Lead cutting-edge research and development in Generative AI (GenAI) to enhance our fraud detection, device trust and customer data models, including model architecture design, hyperparameter optimization, and evaluation metrics.
  • Fine-tune advanced Large Language Models (LLMs) for domain-specific applications, inference optimization, and multi-agentic workflows, leveraging techniques like transfer learning, prompt engineering, curriculum learning, and reinforcement learning with human feedback (RLHF).
  • Leverage a broad stack of technologies - Python, AWS, Pyspark, LangChain, LangGraph, HuggingFace Transformers, vLLM and VectorDBs, and more, for model development, deployment, and monitoring.
  • Be the expert in Graph ML, and Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for business specific applications and features, including entity recognition, sentiment analysis, and summarization.
  • Drive innovation by designing, training, evaluating, and deploying state-of-the-art AI models, partnering with engineering teams to integrate them into scalable and resilient production systems with robust MLOps practices.
  • Translate complex AI/ML research into tangible business outcomes, improving customer experience through real-time, intelligent digital assistance, by identifying key performance indicators (KPIs) and designing A/B tests to measure impact.
  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 9 years of experience performing data analytics.
  • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 7 years of experience performing data analytics.
  • A PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 4 years of experience performing data analytics.
  • At least 4 years of experience leveraging open source programming languages for large scale data analysis.
  • At least 4 years of experience working with machine learning.
  • At least 4 years of experience utilizing relational databases.
  • PhD in Computer Engineering plus 8 years of relevant experience, prior publication/research experience referred.
  • At least 4 years of specialized experience in GenAI application development.
  • At least 4 years of experience in LLM model training, evaluation, inference optimization and parallelization in GPU cluster.
  • At least 5 years of experience working with AWS or equivalent GPU Clusters.
  • At least 5 years of experience in PyTorch/Tensorflow.
  • Comprehensive health benefits.
  • Financial benefits including performance-based incentive compensation.
  • Inclusive set of benefits that support total well-being.
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