Capital One
Senior Director, Data Science - Customer Core Specialist Models
Capital One, San Jose, California, United States, 95199
Overview
Senior Director, Data Science - Customer Core Specialist Models
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by personalizing every credit card offer using statistical modeling and the relational database. This innovation helped our growth to a Fortune 200 company and a leader in data-driven decision-making. As a Data Science Leader at Capital One, you will be part of a team that's driving the next wave of AI-driven disruption at scale, using the latest computing and AI/ML technologies on billions of customer records to help people save money, time, and reduce financial friction.
Team Description The Specialist Models Team in AI Foundations engages in active research in GenAI and AI-powered capabilities to build scalable solutions that enhance our customers’ digital experience and protect their financial lives. You will lead research, innovation, and development of applications with emerging AI/ML technologies. Research areas include advanced LLM-powered search, natural language interfaces, biometrics, recommendation and personalization systems, highly sensitive data detection, guardrails, and red-teaming to build safe and reliable AI systems.
In this role, you will:
Lead a cross-functional team of data scientists, software engineers, and ML engineers, collaborating with product managers and engineers to deliver AI-powered products.
Lead cutting-edge research and development in Generative AI (GenAI) to enhance 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-agent workflows, leveraging transfer learning, prompt engineering, curriculum learning, and reinforcement learning with human feedback (RLHF).
Utilize a broad technology stack (Python, AWS, PySpark, LangChain, LangGraph, HuggingFace Transformers, vLLM, VectorDBs, and more) for model development, deployment, and monitoring.
Be an expert in Graph ML and NLP to harness LLMs for business applications, including entity recognition, sentiment analysis, and summarization.
Design, train, evaluate, and deploy state-of-the-art AI models, partnering with engineering teams to integrate them into scalable production systems with robust MLOps practices.
Translate AI/ML research into tangible business outcomes by identifying KPIs and designing A/B tests to measure impact and improve customer experience through real-time intelligent digital assistance.
The Ideal Candidate is:
Innovative: Deeply engaged in AI/ML research, with a strong understanding of model limitations and ethical considerations.
Creative: Able to solve complex, ambiguous problems and translate business needs into technical requirements.
A leader: Capable of driving breakthroughs, mentoring teams, and fostering a culture of learning and experimentation.
Technical: Hands-on experience with AI/ML development, open-source tools, cloud platforms, DevOps, model lifecycle management, data governance, and explainable AI (XAI).
Influential: Able to communicate complex ideas clearly to technical and non-technical audiences and influence stakeholders.
Basic Qualifications:
Currently has, or is in the process of obtaining, one of the following with an expectation to complete by the start date:
A Bachelor's Degree in a quantitative field plus 11 years of data analytics experience.
A Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 9 years of data analytics experience.
A PhD in a quantitative field plus 6 years of data analytics experience.
At least 6 years of experience leveraging open source programming languages for large-scale data analysis.
At least 6 years of experience working with machine learning.
At least 6 years of experience utilizing relational databases.
Preferred Qualifications:
PhD in Computer Engineering with 10 years of relevant experience; prior publication/research experience is preferred.
At least 5 years of specialized GenAI application development experience.
At least 5 years of experience in LLM model training, evaluation, inference optimization, and parallelization in GPU clusters.
At least 6 years of experience working with AWS or equivalent GPU clusters.
At least 6 years of experience with PyTorch/TensorFlow.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries are offered at the time of hire and may vary by location. Salaries for part-time roles will be prorated based on hours worked.
McLean, VA: $308,700 - $352,300 for Sr Dir, Data Science
New York, NY: $336,700 - $384,200 for Sr Dir, Data Science
San Jose, CA: $336,700 - $384,200 for Sr Dir, Data Science
Candidates hired in other locations will receive the pay range associated with that location and the offer letter will reflect the actual amount.
This role is also eligible to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits. Learn more at the Capital One Careers website. Eligibility varies based on full/part-time status, exempt/non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days. No agencies, please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One promotes a drug-free workplace. Capital One will consider qualified applicants with a criminal history in a manner consistent with applicable laws and regulations.
If you require an accommodation during the application process, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential and used only to provide needed accommodations.
For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com.
Capital One does not provide, endorse, or guarantee third-party products or services and is not liable for information available through this site. Capital One Financial is composed of several entities; postings may refer to Capital One Canada, Capital One Europe, or Capital One Philippines Service Corp, as applicable.
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Data is at the center of everything we do. As a startup, we disrupted the credit card industry by personalizing every credit card offer using statistical modeling and the relational database. This innovation helped our growth to a Fortune 200 company and a leader in data-driven decision-making. As a Data Science Leader at Capital One, you will be part of a team that's driving the next wave of AI-driven disruption at scale, using the latest computing and AI/ML technologies on billions of customer records to help people save money, time, and reduce financial friction.
Team Description The Specialist Models Team in AI Foundations engages in active research in GenAI and AI-powered capabilities to build scalable solutions that enhance our customers’ digital experience and protect their financial lives. You will lead research, innovation, and development of applications with emerging AI/ML technologies. Research areas include advanced LLM-powered search, natural language interfaces, biometrics, recommendation and personalization systems, highly sensitive data detection, guardrails, and red-teaming to build safe and reliable AI systems.
In this role, you will:
Lead a cross-functional team of data scientists, software engineers, and ML engineers, collaborating with product managers and engineers to deliver AI-powered products.
Lead cutting-edge research and development in Generative AI (GenAI) to enhance 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-agent workflows, leveraging transfer learning, prompt engineering, curriculum learning, and reinforcement learning with human feedback (RLHF).
Utilize a broad technology stack (Python, AWS, PySpark, LangChain, LangGraph, HuggingFace Transformers, vLLM, VectorDBs, and more) for model development, deployment, and monitoring.
Be an expert in Graph ML and NLP to harness LLMs for business applications, including entity recognition, sentiment analysis, and summarization.
Design, train, evaluate, and deploy state-of-the-art AI models, partnering with engineering teams to integrate them into scalable production systems with robust MLOps practices.
Translate AI/ML research into tangible business outcomes by identifying KPIs and designing A/B tests to measure impact and improve customer experience through real-time intelligent digital assistance.
The Ideal Candidate is:
Innovative: Deeply engaged in AI/ML research, with a strong understanding of model limitations and ethical considerations.
Creative: Able to solve complex, ambiguous problems and translate business needs into technical requirements.
A leader: Capable of driving breakthroughs, mentoring teams, and fostering a culture of learning and experimentation.
Technical: Hands-on experience with AI/ML development, open-source tools, cloud platforms, DevOps, model lifecycle management, data governance, and explainable AI (XAI).
Influential: Able to communicate complex ideas clearly to technical and non-technical audiences and influence stakeholders.
Basic Qualifications:
Currently has, or is in the process of obtaining, one of the following with an expectation to complete by the start date:
A Bachelor's Degree in a quantitative field plus 11 years of data analytics experience.
A Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 9 years of data analytics experience.
A PhD in a quantitative field plus 6 years of data analytics experience.
At least 6 years of experience leveraging open source programming languages for large-scale data analysis.
At least 6 years of experience working with machine learning.
At least 6 years of experience utilizing relational databases.
Preferred Qualifications:
PhD in Computer Engineering with 10 years of relevant experience; prior publication/research experience is preferred.
At least 5 years of specialized GenAI application development experience.
At least 5 years of experience in LLM model training, evaluation, inference optimization, and parallelization in GPU clusters.
At least 6 years of experience working with AWS or equivalent GPU clusters.
At least 6 years of experience with PyTorch/TensorFlow.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries are offered at the time of hire and may vary by location. Salaries for part-time roles will be prorated based on hours worked.
McLean, VA: $308,700 - $352,300 for Sr Dir, Data Science
New York, NY: $336,700 - $384,200 for Sr Dir, Data Science
San Jose, CA: $336,700 - $384,200 for Sr Dir, Data Science
Candidates hired in other locations will receive the pay range associated with that location and the offer letter will reflect the actual amount.
This role is also eligible to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits. Learn more at the Capital One Careers website. Eligibility varies based on full/part-time status, exempt/non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days. No agencies, please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One promotes a drug-free workplace. Capital One will consider qualified applicants with a criminal history in a manner consistent with applicable laws and regulations.
If you require an accommodation during the application process, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential and used only to provide needed accommodations.
For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com.
Capital One does not provide, endorse, or guarantee third-party products or services and is not liable for information available through this site. Capital One Financial is composed of several entities; postings may refer to Capital One Canada, Capital One Europe, or Capital One Philippines Service Corp, as applicable.
#J-18808-Ljbffr