Senior Manager, Data Science – Model Risk Office

Capital One

. Defend the company against model failures and identify ways to improve model-based decisions .

Posted 10/5/2026full-timeUnited StatesSenior💰 $209,000 - $262,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and validating machine learning models, utilizing Python and AWS for large-scale data analysis, and translating complex technical concepts into actionable business strategies. Proficient in leveraging statistical and analytical tools to enhance model performance and support data-driven decision-making.

Highest-signal resume keywords

Machine Learning DevelopmentPython ProgrammingAWS Cloud ComputingData AnalyticsModel Validation

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningData AnalysisStatistical ModelingModel ValidationClusteringClassificationSentiment AnalysisTime Series AnalysisDeep LearningRelational Databases

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

PythonCondaAWSH2OSpark

Industry Keywords

Data ScienceQuantitative AnalysisOpen Source ToolsCloud ComputingCapital One

Tech Stack

Tools & technologies

AWSCloudOpen SourcePythonScalaSpark

About the role

Key responsibilities & impact

Defend the company against model failures and identify ways to improve model-based decisions
Review and oversee models used for underwriting Capital One credit card products
Use modeling, statistical, monitoring, and analytical tools to govern data science models and support positive business outcomes
Partner with data scientists, software engineers, and product managers to deliver customer-focused products
Use Python, Conda, AWS, H2O, Spark, and other technologies to analyze large volumes of numeric and textual data
Build machine learning models through design, training, evaluation, validation, and implementation
Translate complex technical work into tangible business goals
Research and evaluate emerging technologies and apply state-of-the-art methods

Requirements

What you’ll need

Currently has, or is in the process of obtaining, a required quantitative degree by the scheduled start date
Bachelor's degree in a quantitative field plus 7 years of experience performing data analytics, or Master's degree/MBA with quantitative concentration plus 5 years, or PhD in a quantitative field plus 2 years
At least 2 years of experience leveraging open source programming languages for large scale data analysis
At least 2 years of experience working with machine learning
At least 2 years of experience utilizing relational databases
Hands-on experience developing data science solutions using open-source tools and cloud computing platforms
Experience building, validating, and backtesting models
Experience with clustering, classification, sentiment analysis, time series, and deep learning
Ability to retrieve, combine, and analyze data from varied sources and structures
Capital One will consider sponsoring a new qualified applicant for employment authorization
Preferred: PhD in STEM plus 4 years of experience in data analytics
Preferred: at least 1 year of AWS experience
Preferred: at least 1 year of people-management experience
Preferred: at least 5 years of Python, Scala, or R for large scale data analysis
Preferred: at least 5 years of machine learning experience

Benefits

Comp & perks

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial and other benefits supporting total well-being
Reasonable accommodations for applicants who require them