Principal Data Scientist - Applied Research

Team 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, such as generative AI and continuous self-learning, while addressing 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:

• Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
• Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
• 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.
• Technical. 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 platforms.
• 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, platform level code or solution level code to existing products.
• 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:

• Bachelor’s Degree plus 5 years of experience in Data Analytics, or Master’s Degree plus 3 years of experience in Data Analytics, or PhD
• At least 1 year of experience in AI research
• At least 2 years of experience with Deep Learning
• At least 2 years experience in developing and debugging in C/C++, Python, or C#

Preferred Qualifications:

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 2 years of experience in applied AI research
• At least 1 year of experience with LLM practices such as prompt engineering, supervised fine tuning, distillation
• At least 2 years of experience in interdisciplinary research collaborations
• At least 1 year of experience showing first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL)

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.

San Francisco, California:

$171,500 - $195,800 for Data Science PhD

New York City:

$161,900 - $184,800 for Data Science PhD