Manager, Data Science - US Card - Marketing

Manager, Data Science - US Card - Marketing

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

The Marketing Data Science team develops advanced machine learning solutions designed to optimize customer acquisition. By deploying predictive models and reinforcement learning across critical touchpoints in the marketing funnel, we deliver personalized customer experiences that accelerate growth. Our core focus is embedding model-driven insights across every channel to ensure seamless, highly targeted engagement.

To achieve this, we use supervised and reinforcement learning models to predict customer needs and recommend optimal solutions. We write custom Python libraries and use open-source ML libraries like XGBoost, scikit-learn, and statsmodels. Our models define the treatment for millions of customers on a daily basis and your code will run in analytical and production environments.

We collaborate closely with campaign managers, business analysts, and engineering teams to ensure our models generate measurable business value and directly inform strategic decisions.

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 implementation
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals
• This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location.

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.
• 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 faze 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.

Basic

Qualifications

• 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 6 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 4 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) plus 1 year of experience performing data analytics
• At least 1 year of experience leveraging open source programming languages for large scale data analysis
• At least 1 year of experience working with machine learning
• At least 1 year of experience utilizing relational databases

Preferred

Qualifications

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
• 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

Cambridge, MA: $197,300 - $225,100 for Mgr, Data Science

McLean, VA: $197,300 - $225,100 for Mgr, Data Science

New York, NY: $215,200 - $245,600 for Mgr, Data Science