Job Specifications
Senior Manager, Data Science - GenAI Digital Assistant
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 a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning 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 GenAI Powered Digital Assistant Team in AI Foundations engage in active research in GenAI powered conversational capabilities and build scalable futuristics solutions to enhance our customers digital experience and Real Time support through digital assistance. 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 digital Assistant, multi-agentic workflow, domain specific conversational large language model tuning and inference optimization. In this role, you will
Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how developers write software.
Lead cutting-edge research and development in Generative AI (GenAI) to enhance conversational AI capabilities and build scalable, futuristic digital assistant solutions.
Fine-tune advanced Large Language Models (LLMs) for domain-specific conversational applications, inference optimization, and multi-agentic workflows.
Leverage a broad stack of technologies - Python, AWS, Pyspark, LangChain, LangGraph, HuggingFace Transformers, vLLM and VectorDBs, and more
Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for business specific applications and features.
Drive innovation by designing, training, evaluating, and deploying state-of-the-art NLP models, partnering with engineering teams to integrate them into scalable and resilient production systems.
Translate complex AI/ML research into tangible business outcomes, improving customer experience through real-time, intelligent digital assistance. The Ideal Candidate is
Innovative. You are deeply engaged in AI/ML research and stay ahead of the curve on emerging GenAI advancements. You seek out opportunities to apply state-of-the-art methods to real-world problems.
Creative. You excel at defining and solving complex, ambiguous problems, constantly questioning and pushing boundaries to develop novel solutions
A leader. You challenge conventional thinking, drive breakthroughs in conversational AI, and mentor teams to achieve innovation excellence
Technical. You have hands-on experience in AI/ML development, working with open-source tools, cloud computing platforms, and DevOps technologies. You are proficient in NLP and LLM tuning.
Influential. You are passionate about GenAI and can bring together cross-functional teams to drive adoption and innovation. You communicate complex ideas clearly to technical and non-technical audiences. Basic Qualifications
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 7 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 5 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 2 years of experience performing data analytics
At least 2 years of experience leveraging open source programming languages for large scale data analysis
At least 2 years of experience working with machine learning
At least 2 years of experience utilizing relational databases Preferred Qualifications
PhD in Computer Engineering plus 4 years of relevant experience, prior publication/research experience referred
At least 3 years of specialized experience in GenAI application development.
At least 3 years of experience in LLM model training, evaluation, inference optimization and parallelization in GPU cluster
At least 3 years of experience w