McLean 1 (19050), 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 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 Credit Risk Management, Loss Forecasting and Allowance team uses machine learning models to forecast and optimize future losses associated with Capital One's credit card portfolio. We work with the Center of Machine Learning to use the latest technologies and algorithms to build predictive models and automate insight generation.
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 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:
* Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.
* 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. Your 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 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 2 years of experience in data analytics, or Master's Degree plus 1 year of experience in data analytics, or PhD
* At least 1 year of experience in open source programming languages for large scale data analysis
* At least 1 year of experience with machine learning
* At least 1 year of experience with relational databases
* Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 1 year of experience in data analytics, or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)
* 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
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.