Capital One National Association
Principal Associate, Data Scientist – People Strategy & Analytics
Data is at the center of everything we do. As a startup, we disrupted the credit‑card industry by individually personalizing every offer using statistical modeling and relational databases, cutting edge technology in 1988! Today, that innovation and our passion for data have propelled us to a Fortune 200 company and a leader in 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 frustration in their financial lives.
Team Description People Strategy & Analytics is an emerging field where Capital One is at the forefront. The team combines data, analytics, and insights to shape critical talent decisions and strategy. We work closely with HR partners and senior executives to automate real‑time data and improve talent decision‑making. The team is comprised of data analysts, engineers, product managers, data scientists, consultants and strategists, business analysts, HR specialists, economists, and industrial‑organizational psychologists.
Role Description
Attracting, developing, and retaining top talent
Ensuring a phenomenal associate experience
Building a high‑performing, highly diverse executive pipeline
Maximizing productivity
Rethinking how we measure talent
Human capital problems require particular attention to sample size impacts, covariance, selection bias, modeling choices, and other issues that can be the difference between highly meaningful & impactful results and noise. In this role, you will leverage structured problem‑solving approaches and data science skills to identify and deliver high‑impact solutions, as well as develop unique data science skills and human‑capital expertise.
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 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
Translate the complexity of your work into tangible business goals and collaborate across the organization
The Ideal Candidate Is:
Passionate about human capital : Excited by the value we can add to our company and associates, and inspired to make a large positive impact
Innovative : Continuously research and evaluate emerging technologies, stay current on state‑of‑the‑art methods, and seek opportunities to apply them
Creative : Thrive on defining big, undefined problems; love asking questions and pushing hard to find answers; not afraid to share new ideas
Technical : Comfortable with open‑source languages, passionate about developing further, and experienced in cloud‑based data science solutions
Statistically‑minded : Built models, validated them, and backtested; knows how to interpret a confusion matrix or ROC curve; experienced with clustering, classification, sentiment analysis, time series, and deep learning
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 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 (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in STEM
At least 1 year of experience working with AWS
At least 3 years’ experience in Python, Scala, or R
At least 3 years’ experience with machine learning
At least 3 years’ experience with SQL
Compensation McLean, VA: $158,600 – $181,000 for Principal Associate, Data Science. The role is also eligible to earn performance‑based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI).
EEO Statement Capital One is an equal‑opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace and will consider qualified applicants with a criminal history in a manner consistent with applicable laws.
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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 frustration in their financial lives.
Team Description People Strategy & Analytics is an emerging field where Capital One is at the forefront. The team combines data, analytics, and insights to shape critical talent decisions and strategy. We work closely with HR partners and senior executives to automate real‑time data and improve talent decision‑making. The team is comprised of data analysts, engineers, product managers, data scientists, consultants and strategists, business analysts, HR specialists, economists, and industrial‑organizational psychologists.
Role Description
Attracting, developing, and retaining top talent
Ensuring a phenomenal associate experience
Building a high‑performing, highly diverse executive pipeline
Maximizing productivity
Rethinking how we measure talent
Human capital problems require particular attention to sample size impacts, covariance, selection bias, modeling choices, and other issues that can be the difference between highly meaningful & impactful results and noise. In this role, you will leverage structured problem‑solving approaches and data science skills to identify and deliver high‑impact solutions, as well as develop unique data science skills and human‑capital expertise.
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 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
Translate the complexity of your work into tangible business goals and collaborate across the organization
The Ideal Candidate Is:
Passionate about human capital : Excited by the value we can add to our company and associates, and inspired to make a large positive impact
Innovative : Continuously research and evaluate emerging technologies, stay current on state‑of‑the‑art methods, and seek opportunities to apply them
Creative : Thrive on defining big, undefined problems; love asking questions and pushing hard to find answers; not afraid to share new ideas
Technical : Comfortable with open‑source languages, passionate about developing further, and experienced in cloud‑based data science solutions
Statistically‑minded : Built models, validated them, and backtested; knows how to interpret a confusion matrix or ROC curve; experienced with clustering, classification, sentiment analysis, time series, and deep learning
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 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 (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in STEM
At least 1 year of experience working with AWS
At least 3 years’ experience in Python, Scala, or R
At least 3 years’ experience with machine learning
At least 3 years’ experience with SQL
Compensation McLean, VA: $158,600 – $181,000 for Principal Associate, Data Science. The role is also eligible to earn performance‑based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI).
EEO Statement Capital One is an equal‑opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace and will consider qualified applicants with a criminal history in a manner consistent with applicable laws.
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