Manager, Data Scientist -Financial Services- Pricing

Capital One • McLean, VA

6d • $179,400 - $204,700

About The Position

Capital One seeks a Manager, Data Scientist for Financial Services Pricing. The role is part of a data science team applying statistical modeling, machine learning, and large-scale data analysis to support customer-focused products and business decisions. The Data Scientist partners with data scientists, software engineers, and product managers, and uses technologies including Python, Conda, AWS, H2O, and Spark to find insights in large volumes of numeric and textual data. The role builds machine learning models throughout the development lifecycle, from design and training through evaluation, validation, and implementation, and communicates technical work in terms of tangible business goals.

The ideal candidate is customer-focused, innovative, creative, and a leader who works with stakeholders to improve existing approaches and supports talent development. They are technically proficient with open-source languages and cloud computing, statistically minded, and experienced in building, validating, and backtesting models. Relevant methods include clustering, classification, sentiment analysis, time series, and deep learning. They can retrieve, combine, and analyze data from varied sources and structures.

Requirements

• Currently hold, or be in the process of obtaining by the scheduled start date, a bachelor's degree in a quantitative field plus 6 years of data analytics experience; a master's degree in a quantitative field or an MBA with a quantitative concentration plus 4 years of data analytics experience; or a PhD in a quantitative field plus 1 year of data analytics experience.
• 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.
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• Experience building, validating, and backtesting models; interpreting confusion matrices or ROC curves; and working with methods such as clustering, classification, sentiment analysis, time series, and deep learning.
• Ability to retrieve, combine, and analyze data from a variety of sources and structures.

Nice To Haves

• PhD in a STEM field plus 3 years of data analytics experience.
• At least 1 year of experience working with AWS.
• At least 4 years of experience using Python, Scala, or R for large-scale data analysis.
• At least 4 years of experience with machine learning.
• At least 4 years of experience with SQL.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver products customers love.
• Use technologies such as Python, Conda, AWS, H2O, and Spark to derive insights from large volumes of numeric and textual data.
• Build machine learning models across the development lifecycle, including design, training, evaluation, validation, and implementation.
• Translate complex technical work into tangible business goals.
• Work with stakeholders to identify and improve the status quo.
• Support talent development for the team and beyond.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager