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.
Senior Manager Data Science- Model Risk
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.
In Capital One's Model Risk Office, we defend the company against the failure of models that are the foundation of our multi-billion dollar business and meet the needs of tens of millions of customers every day. Model failures happen in a fascinating nexus of people, management and incentive structures, processes, technology, feedback loops, and unexpected external events. It is our job to learn from past mistakes and develop techniques to avoid their repetition. We get broad enterprise visibility to a diverse array of modeling applications from Cybersecurity to Chatbots to Credit Risk, and directly advise and influence senior executives.
Today, Capital One is transforming its data infrastructure and modeling methodologies to build on its competitive advantage as a "Machine Learning company". This gives us an unprecedented opportunity to cultivate best practices and project them throughout the company. The Model Risk Office curates business intent and serves as a center of excellence that drives R&D for tools and platforms that enable Analysts across the Enterprise to deliver business-critical analytics to the cloud while maintaining high standards for quality and risk management.
In this role, you will:
-Build benchmark and challenger models to stress test critical modeling decisions
-Develop and defend techniques for evaluating model performance
-Read up on or even develop a new modeling algorithm
-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
-Evaluate deployment architecture and code quality for a new machine learning system
-Flex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
-Innovative Technically. You're comfortable with open-source languages and are passionate about developing further. 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.
-Creativity and Curiosity. 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.
-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 phase 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.
Bachelor's Degree plus 7 years of experience in data analytics, or Master's Degree plus 5 years of experience in data analytics, or PhD plus 2 years of experience in data analytics
At least 3 years' experience in open source programming languages for large scale data analysis
At least 3 years' experience with machine learning
At least 3 years' experience with relational databases
PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics
At least 1 year of experience working with AWS
At least 1 year of experience managing people
At least 5 years' experience in Python, Scala, or R for large scale data analysis
At least 5 years' experience with machine learning
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Capital One is an equal opportunity employer committed to diversity in the workplace. Capital One promotes a drug-free workplace.
All qualified applicants will receive consideration for employment without regard to gender, race, color, religion, national origin, sexual orientation, protected veteran status, or disability status.
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; Newark, New Jersey Ordinance 12-1630; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.