Capital One Principal Associate Data Scientist - Audit Science 

United States, Virginia, Richmond 

374070829

Principal Associate, Data Scientist - Audit Data Science

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, software engineers, and product managers to deliver a product customers love

• Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data

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

• 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.

• Statistically-minded. You’ve built models, validated them, and backtested 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.

Basic Qualifications:

• Currently has, or is in the process of obtainingone of the followingwith 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 5 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 plus 3 years of experience performing data analytics

  • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Preferred Qualifications:

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)

• At least 3 years of experience in Python, Scala, or R

• At least 3 years of experience with machine learning

• At least 3 years of experience with SQL

• At least 3 years of experience working with Natural Language Processing models (e.g., Transformers)

• At least 1 year of experience working with AWS

McLean, VA: $158,600 - $181,000 for Princ Associate, Data Science Richmond, VA: $144,200 - $164,600 for Princ Associate, Data ScienceThis 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.

. 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 . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.