Principal Associate , Data Science - Applied Generative AI for Calls and Documents

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 Servicing Intelligence data science team leverages deep learning model architectures to help our internal customers use unstructured, multi-modal data sources - text, image, and audio data. We partner with product, tech, and business teams to deliver solutions spanning from using generative AI to conduct information extraction on millions of document images to analyzing call transcripts to identify customer pain points. You will be the driving force to experiment, innovate, and create next generation experiences powered by the latest emerging generative AI technologies.

Role Description:

In this role, you will:

• Harness the power of transformer model architectures to automatically identify emerging customer pain points in millions of call transcripts.

• Fine-tune large language models (LLMs) and large multi-modal models (LMMs) for extractive and abstractive tasks to search for complex evidence statements in unstructured, multi-page, documents images.

• Manage large scale data annotation projects by guiding frontline agents to curate high quality datasets, delivering model improvements by proposing, managing, and monitoring improvements to data collection processes.

• Work on a team of data scientists to build practical machine learning solutions through all phases of development, including designing, training, evaluating, and monitoring models.

• Communicate frequently with business stakeholders, including everything from brainstorming verbiage to include in a prompt engineering experiment to ascertaining which model evaluation metric best aligns data science outputs with business objectives.

• Collaborate with machine learning engineers to develop, deploy, troubleshoot, optimize, and maintain model pipelines with activities spanning from building reusable Kubeflow components for LLM fine-tuning to conversing about the cost impacts of model architecture choices.

• Leverage a broad stack of technologies including Pytorch, Hugging Face, LangChain, LLaMA-Factory, GitHub, AWS and more, to automate workflows using huge volumes of text audio, and vision data

The Ideal Candidate is:

• 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.

• 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.

• Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

• Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve.

• Passionate about the applied use of data science - when you see a new generative model take the top spot on a HuggingFace model leaderboard, you are just as excited about how it can improve a business process as you are about the underlying technical innovations.

• You have an ownership mindset for all upstream and downstream impacts to model pipelines. You like to question what imperfections exist in a model benchmark, taking self-initiative to fix data quality issues in evaluation data.

Basic Qualifications:

• Currently has, or is in the process of obtaining a Bachelor's Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master's Degree plus 3 years of experience in data analytics, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date

• At least 1 year of experience in open source programming languages for large scale data analysis

• At least 1 year of experience with machine learning

• At least 1 year of experience with relational databases

Preferred Qualifications:

• At least 2 years of experience working with unstructured data for either natural language processing, computer vision or speech applications

• At least 2 years of experience fine-tuning and deploying transformer based models using deep learning libraries and tools such as Pytorch and HuggingFace

• At least 3 years of experience with object oriented Python via experiences in data science and software engineering

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): $165,100 - $188,500 for Princ Associate, 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 will consider sponsoring a new qualified applicant for employment authorization for this position.

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.

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

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Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).