Capital One Data Science Manager in McLean, Virginia
McLean 2 (19052), United States of America, McLean, Virginia
At Capital One, we’re building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.
Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.
Data Science Manager
Manager Data Scientist, Small Business Bank
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.
The Small Business Bank DS team builds the machine learning models that help our business partners design and deliver products and policies that meet small businesses’ needs and expectations in financial services. We do models and test design to inform policies and develop segmentation strategies for marketing, using multiple cloud-based open-sourced tech stacks.
In this role, you will:
Partner with a cross-functional team of data scientists, software engineers, business analysts and product managers to manage risk while delivering products for customers
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
The Ideal Candidate is:
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.
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.
Bachelor’s Degree plus 4 years of experience in data analytics, or Master’s Degree plus 2 years of experience in data analytics, or PhD
At least 2 years’ experience in open source programming languages for large scale data analysis
At least 2 years’ experience with machine learning
At least 2 years’ experience with relational databases
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
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
At least 4 years’ experience with SQL
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.