Manager, Data Scientist, Bureau Data Strategy

About the Role

Data is central to Capital One's operations. The Bureau Data Strategy team is responsible for generating insights, extracting value from Bureau Data, and shaping the future of how credit bureau data is used in underwriting at Capital One. This team produces highly-used datasets from raw credit bureau data.

Key Responsibilities

• 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, Spark, and more to reveal insights within large volumes of numeric and textual data.
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
• Translate complex work into tangible business goals.

Requirements & Tech Stack

• Python, Conda, AWS, H2O, Spark.
• Open-source languages and tools.
• Cloud computing platforms.
• Relational databases.
• GitHub (preferred).
• Spark or PySpark (preferred).

Qualifications

Currently have, or in the process of obtaining, a degree with an expectation that it will be obtained on or before the scheduled start date.

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 4 years of experience in Python, Scala, R, or SQL for large scale data analysis.
• At least 4 years of experience with machine learning.
• At least 2 years of experience with managing production repositories on GitHub.
• At least 1 year of experience working with Spark or PySpark.