Data Science Senior Director - AI Foundations

Key Skills

Aartificial intelligence, AWS, Computer Vision (CV), Data Analysis, Data Analytics, Data science techniques, Design, Large Language Models - LLMs, Machine learning techniques, Optimization, Python Programming, PyTorch, R Programming, Scala Programming

Job Description

The AI Foundations team partners with product, tech, and business leaders to advance and deliver on our strategic vision to harness emerging AI advances. This team will address fundamental invention challenges in AI for data (discovery, redaction, cleansing) and data for AI (fusing across sources, types, quality). 

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 customers interact with their money.

• Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.

• Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.

• Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.

• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The Ideal Candidate:

• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.

• You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing.

• Has a deep understanding of the foundations of AI methodologies.

• Experience building LLMs or large computer vision models as well as expertise in one or more key subdomain such as: training optimization, self-supervised learning, robustness, explainability, RLHF.

• An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.

• Experience in delivered libraries

• A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.

• Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.

Basic Qualifications:

• Currently has, or is in the process of obtaining a Bachelor’s Degree plus 9 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 7 years of experience in data analytics, or currently has, or is in the process of obtaining a PhD plus 4 years of experience in data analytics

• At least 4 years of experience in open source programming languages for large scale data analysis

• At least 4 years of experience with machine learning

• At least 4 years of experience with relational databases

Preferred Qualifications:

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics

• At least 1 year of experience working with AWS

• At least 3 year of experience managing people

• At least 5 years of experience in Python, Scala, or R for large scale data analysis

• At least 5 years of experience with machine learning

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. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

New York City (Hybrid On-Site): $321,500 - $366,900 for Sr Dir, Data Science; $274,800 - $313,600 for Dir, Data Science

San Francisco, California (Hybrid On-Site): $340,500 - $388,700 for Sr Dir, Data Science; $291,100 - $332,300 for Dir, Data Science

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) 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 that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com