Manager, Data Scientist

About the Role

Data is central to Capital One's operations. As a Data Scientist, you will be part of a team driving disruption using the latest computing and machine learning technologies, processing billions of customer records to unlock opportunities that help people save money, time, and agony in their financial lives. The US Card Data Science team develops industry-leading machine learning models for core underwriting decisions in credit card acquisitions and management. The team collaborates with data engineers, platform engineers, product managers, and credit and business analysts, owning the full lifecycle of models from development to deployment, monitoring, and governance.

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 including Python, Conda, AWS, H2O, and Spark to reveal insights from large volumes of numeric and textual data.
• Build machine learning models through all phases of development: design, training, evaluation, validation, and implementation.
• Utilize interpersonal skills to translate complex work into tangible business goals.

Key Responsibilities

• Partner with a cross-functional team.
• Leverage a broad stack of technologies.
• Build machine learning models.
• Translate complexity into business goals.

Requirements & Tech Stack

• Python, Conda, AWS, H2O, Spark
• Relational databases

Qualifications

Basic Qualifications

• 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.
• 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.
• 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 a "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.