Data Scientist, Credit Review TeamApply now Job ID R77122 Updated date 06/28/2019 Location 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 in Credit Review, you’ll be part of a team that’s an industry leader in managing credit risk with next generation of modeling and technology. With a network of over 200 Quants and Data Scientists in the company and credit lending experts on the team, we’ve created a dynamic environment with plenty of room for you to learn, grow, and realize your full potential.
In this role, you will:
· Partner with a cross-functional team of quants/data scientists, business analysts, and product managers to change the way we do business
· Leverage a broad stack of technologies — Python, R, 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
· Influence senior leaders in advancing credit risk management and modeling techniques to gain risk insight
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. 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 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 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.No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. 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.
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