Principal Associate, Data Scientist - Deposit Forecasting and Pricing

Requirements

• 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 5 years of experience performing data analytics
• 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 3 years of experience performing data analytics
• A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)
• Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years 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
• 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.
• McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science
• Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candi

Additional Information

Principal Associate, Data Scientist - Deposit Forecasting and Pricing 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. Team Description As a Data Scientist at the Retail and Direct Bank, you'll be part of a high performing modeling and analytics team that is on a mission to define the next generation of banking. The Bank team has a relentless focus on the craft of statistical modeling and innovation with a target towards continually improving decision making and delivering value to the business. Role Description This role offers a unique opportunity to be part of a dynamic analytics and modeling team focused on developing behavior models for balance sheet portfolios. We are currently looking for candidates with strong modeling and analytical skills. This position will work with other quantitative analysts, data scientists, and the business analysts in developing and enhancing the deposit modeling framework to support multiple business purposes in Capital One. Responsibilities and Skills: Develop and support econometric time-series models for the balance sheet Identify opportunities to apply quantitative methods to improve business performance Demonstrate track record in behavior model development Ability to clearly communicate models and methods to management, model risk office, regulators and other modelers Develop and maintain high quality and transparent documentation 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. 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.

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