Innovation is at the heart of everything we do on the Audit Analytics and Innovation team. We’re not a traditional Data Science team: we build creative ML solutions across multiple domains, such as LLM based chatbots, GenAI powered applications, AML/Fraud identification, and Customer call transcripts intelligence. Opportunities to learn and build fast allow our team members to develop towards their full potential. We partner closely with product, tech, and design teams to enable faster build-to-market cycles for product features that delight our customers with dynamic and integrated experiences. 

You will be the driving force to experiment, innovate, and create next-generation features powered by the latest emerging NLP and Generative AI technologies. If you love a fast-paced, highly rewarding environment, and you love being a builder and communicator, this is the place for you.

In this role, you will:

• Partner with a cross-functional team of data scientists, data analysts, risk professionals, software engineers, and product managers to manage risk and uncertainty in order to lead Capital One to the best decisions, not just avoid the worst ones 

• Leverage a broad stack of technologies (Python, Conda, Flask, Dash, Hugging Face, LangChain, AWS, H2O, Spark, and more) to reveal the insights hidden within huge volumes of numeric and textual data

• Build machine learning and NLP models through all phases of development, from design through training, evaluation, validation, and implementation.

• Productionize highly scalable data pipelines for faster feature changes and updates, and implementing data validation framework and quality tests 

• Develop visualization tools to streamline model monitoring reports 

• Investigate new technology to advance data management, model development and deployment and drive change in enterprise ML products 

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

The Ideal Candidate is:

• 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.

• 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.

• Collaboration and Communication. You’re capable of effectively articulating data insights and analytics strategies to a diverse audience, including auditors, engineers, product managers and leadership. 

• Statistically-minded. You’ve built models, validated them, and back tested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.

• A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

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 2 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

Preferred Qualifications:

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)

• Experience working with AWS

• At least 2 years of experience in Python, Scala, or R

• At least 2 years of experience with machine learning

• At least 2 years of experience with SQL 

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.

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.

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.