Manager, Data Scientist - Credit Review
Company: Capital One
Location: Mc Lean
Posted on: April 2, 2026
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Job Description:
Manager, Data Scientist - Credit Review 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 In
Capital One’s Credit Review Models, Data and Innovative solutions
team, we defend the company against model failures and find new
ways of making better decisions with models. We use our statistics,
software engineering, and business expertise to drive the best
outcomes in both Risk Management and the Enterprise. We understand
that we can’t prepare for tomorrow by focusing on today, so we
invest in the future: investing in new skills, building better
tools, and maintaining a network of trusted partners. We partner
with best-in-class data scientists, analysts, credit risk
management experts, and engineers to innovate solutions that
directly impact the company’s bottom line in a meaningful way. We
do it all in a collaborative environment that values individual
insight, encourages each associate to take on new responsibilities,
promotes continuous learning, and rewards innovation. Role
Description In this role, you will: Leverage a broad stack of
technologies, such as, Python, Conda, AWS, H2O, Spark, and more, to
reveal the insights hidden within huge volumes of numeric and
textual data Build statistical and machine learning models to
challenge the models in production Flex your interpersonal skills
to translate the complexity of your work into tangible business
goals Partner with a cross-functional team of data scientists,
credit risk experts, and product managers to deliver a product
customers love The Ideal Candidate is: 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.
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. 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 databases Preferred Qualifications: PhD in “STEM” field
(Science, Technology, Engineering, or Mathematics) plus 3 years of
experience in data analytics At least 4 years’ experience in
Python, Scala, or R for large scale data analysis At least 4 years’
experience with machine learning At least 4 years’ experience with
predictive modeling 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. Sales Territory: $179,400 - $204,700 for Mgr, Data Science
Plano, TX: $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 Riverwoods, IL: $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, Montgomery Village , Manager, Data Scientist - Credit Review, IT / Software / Systems , Mc Lean, Maryland
