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About the Role

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 AI 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. We're building a portfolio of agentic AI products to transform Capital One's engineering organizations and lines of business. We're creating a new science team to help define the long-term strategy, analyze & optimize impact throughout the ecosystem, and drive business value at enterprise scale. As a scientist on the team, you'd design AI/ML models and help build the solutions behind these products. You'd also own the science that guides them: designing experiments (A/B tests), modeling telemetry, and turning the results into AI strategy and guidance for C-suite leadership.

Responsibilities

Partner with a cross-functional team of data scientists, AI & ML engineers, and product managers to deliver enterprise products 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

Requirements

Customer first: You love the process of analyzing and creating, but also share our passion to do the right thing.
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.
A leader: You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
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.
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 9 years of experience performing data analytics
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 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 7 years of experience performing data analytics
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 PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 4 years of experience performing data analytics
At least 4 years of experience leveraging open source programming languages for large scale data analysis
At least 4 years of experience building/deploying AI/ML models in production
At least 4 years of experience designing and analyzing A/B tests
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
3+ years of experience working with AWS
5+ years of experience in Python, Scala, or R for large scale data analysis
5+ years of experience with machine learning
5+ years of experience with Spark

Skills

Python
Conda
AWS
H2O
Spark
Clustering
Classification
Sentiment Analysis
Time Series
Deep Learning
Open-source programming languages
AI/ML models
A/B tests
Data analytics
Machine learning
Scala
R

Location

Cambridge, MA
McLean, VA
New York, NY
Richmond, VA
San Francisco, CA

Work Type

Full-time

Experience Level

9 years of experience performing data analytics
7 years of experience performing data analytics
4 years of experience performing data analytics
4 years of experience leveraging open source programming languages for large scale data analysis
4 years of experience building/deploying AI/ML models in production
4 years of experience designing and analyzing A/B tests
5 years of experience in data analytics
3+ years of experience working with AWS
5+ years of experience in Python, Scala, or R for large scale data analysis
5+ years of experience with machine learning
5+ years of experience with Spark

Education Level

Bachelor's Degree in a quantitative field
Master's Degree in a quantitative field or an MBA with a quantitative concentration
PHD in a quantitative field
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)

Salary/Compensations

Cambridge, MA: $269,100 - $307,200
McLean, VA: $269,100 - $307,200
New York, NY: $293,600 - $335,100
Richmond, VA: $244,700 - $279,200
San Francisco, CA: $293,600 - $335,100

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
Eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).

About the Company

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.

Equal Opportunity

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.