Retail Bank Price and Policy Optimization Data Science Lead - Senior Manager

Center 2 (19050), United States of America, McLean, Virginia

Retail Bank Price and Policy Optimization Data Science Lead - Senior Manager

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.

As the price and policy optimization lead 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. This role offers a unique opportunity to contribute to the growth of our savings and checking portfolios. We are looking for a candidate to help create pricing strategies using numerical optimization and simulation techniques to profitably fund the company. Similarly, this candidate will be responsible for optimizing our checking product policies to enable product differentiation and improve customer experience. We are currently looking for candidates with strong modeling, optimization and analytical skills. This position will also work with other quantitative analysts, data scientists, and the business analysts in enhancing the deposit modeling frameworks.

Role Description
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 implementationFlex your interpersonal skills to translate the complexity of your work into tangible business goals

The Ideal Candidate is:

• 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.

• 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.

Basic Qualifications:

• Currently has, or is in the process of obtaining a Bachelor’s Degree plus 7 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 2 years of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date

• 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

Preferred Qualifications:

• 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

• Experience in using numerical optimization to solve business problems

• Experience with linear, non-linear, integer programming techniques and software packages