Data Science Lead - Small Business Card

Key Skills

Java Programming, Design, Python Programming, Database, SQL, AWS, Big Data Technology, Scala Programming, Machine learning techniques, Data science techniques, Data Analytics, R Programming, SPARK Programming, Mathematics, H2O, Data Analysis

Job Description

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:

Emerging Merchant Businesses is a new team dedicated to discovering and accelerating high-growth opportunities at Capital One. Our newly formed organization is composed of incredibly exciting Capital One businesses, including Capital One Shopping, Flex Pay, and Apollo. As part of the EMB team, you will work alongside experts across customer experience, data, technology (and more!) who are moving quickly to find the next big business at the company. We are looking for talented associates who are motivated to be part of this journey and help us shape the future of Capital One, growing and learning with a team who will invest in your development, foster an inclusive environment, and lead with heart to change banking for good.

As a Manager Data Scientist on the Apollo team in Emerging Merchant Businesses, you are a part of a team that develops the core technology which drives our industry-leading understanding of the U.S. business landscape, generating valuable business insight from many disparate sources. The Apollo team is building technology that allows us to acquire, understand, and make inferences on large, disparate business data sets. This requires ideas from across the machine learning skillset, applied to problems and data that are unique to our business. You will do it all in a collaborative environment that values your insight, encourages you to take on new responsibilities, promotes continuous learning, and rewards innovation.

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, 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:

• 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.
• 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.
• 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.

Capital One is open to hiring a Remote Employee for this opportunity.

Basic Qualifications:

• Bachelor’s Degree plus 6 years of experience in data analytics, or Master’s Degree plus 4 years in data analytics, or PhD plus 1 year of experience in data analytics
• At least 2 years of experience in open source programming languages for large scale data analysis
• At least 2 years of experience with machine learning
• At least 2 years of experience with 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 1 year of experience with version control, CI/CD, and containerization/deployment technologies
• 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