Manager, Data Scientist - Model Risk Office
Company: Capital One
Location: Mc Lean
Posted on: April 1, 2026
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Job Description:
Manager, Data Scientist - Model Risk Office 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
Capital One Model Risk Office is dedicated to safeguarding the
company from model failures while simultaneously enhancing
decision-making through models, including unique risks associated
with Generative AI (GenAI). Leveraging expertise in statistics,
software engineering, and business, we strive to achieve optimal
results for both Risk Management and the broader Enterprise. We
prioritize long-term success by continually investing in future
capabilities: acquiring new skills, developing superior tools, and
cultivating strong relationships with trusted partners. Our
approach involves learning from past errors to develop increasingly
robust techniques that prevent recurrence. Role Description In this
role, you will: Partner with a cross-functional team of data
scientists, software engineers, and product managers to identify
and quantify risks associated with models Leverage a broad stack of
technologies — from foundational frameworks (PyTorch, Hugging
Face), to orchestration tools (LangChain, Vector Databases) to
LLMOps, observability platforms, and more — to reveal the insights
hidden within huge volumes of multi-modal data Build machine
learning models to challenge “champion models” that are deployed in
production today and contribute to the model governance framework
for the next generation of models Validate a wide variety of models
across multiple business domains within our Enterprise Services
division, and flex your interpersonal skills to present how
identified model risks could impact the business to executives. 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. 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 6 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 4 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) plus 1 year of experience
performing data analytics At least 1 year of experience leveraging
open source programming languages for large scale data analysis At
least 1 year of experience working with machine learning At least 1
year of experience utilizing relational or vector databases
Preferred Qualifications: PhD in “STEM” field (Science, Technology,
Engineering, or Mathematics) plus 3 years of experience in data
analytics At least 1 year of experience working with AWS At least 4
years’ experience in Python, Scala, or R for large scale data
analysis At least 4 years’ experience with machine learning,
including GenAI At least 4 years’ experience building or validating
models related to fraud detection, digital marketing,
cybersecurity, or sensitive data detection. 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. Chicago, IL: $179,400
- $204,700 for Mgr, Data Science McLean, VA: $197,300 - $225,100
for Mgr, Data Science Richmond, VA: $179,400 - $204,700 for Mgr,
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 (EOE, including disability/vet)
committed to non-discrimination in compliance with applicable
federal, state, and local laws. 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 Capital One
does not provide, endorse nor guarantee and is not liable for
third-party products, services, educational tools or other
information available through this site. 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).
Keywords: Capital One, Charlottesville , Manager, Data Scientist - Model Risk Office, IT / Software / Systems , Mc Lean, Virginia