Manager, Data Scientist, Card Mainstreet

About the Role

Data is at the center of everything at Capital One. As a Data Scientist, you’ll be part of a team leading disruption using the latest in computing and machine learning technologies, operating across billions of customer records to unlock opportunities that help everyday people save money, time, and agony in their financial lives.

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 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

• Customer first: Passionate about doing the right thing for customers.
• Innovative: Continually researches and evaluates emerging technologies and stays current on published state-of-the-art methods, technologies, and applications.
• Creative: Thrives on bringing definition to big, undefined problems and is not afraid to share new ideas.
• A leader: Challenges conventional thinking, works with stakeholders to identify and improve the status quo, and is passionate about talent development.
• Technical: Comfortable with open-source languages and has hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• Statistically-minded: Has built, validated, and backtested models. Understands confusion matrices or ROC curves. Has experience with clustering, classification, sentiment analysis, time series, and deep learning.
• A data guru: Skilled in retrieving, combining, and analyzing data from a variety of sources and structures.

Requirements & Tech Stack

• Open-source programming languages for large-scale data analysis.
• Machine learning.
• Relational databases.
• Python, Conda, AWS, H2O, Spark.

Qualifications

Basic Qualifications

Currently have, or are 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.