Manager, Data Scientist

Capital One National Association; McLean (VA); On-site; USD 197,300 - 225,100; Full time

Benefits offered by this job

Health benefits

Performance-based incentives

Comprehensive benefits package

Job summary

Capital One National Association seeks a Manager, Data Scientist in McLean, VA. You will work with a team of data scientists and engineers to analyze risks associated with models and build machine learning models to enhance data analysis strategies. The ideal candidate has a strong background in data science, machine learning, and using open-source tools. Annual salaries range from $197,300 to $225,100, along with performance-based compensation and comprehensive benefits.

Qualifications

• 6 years experience in data analytics for Bachelor's degree holders.
• 4 years experience in data analytics for Master's degree holders.
• 1 year experience in data analytics for PhD holders.
• Experience with machine learning, open-source languages, and relational databases.

Responsibilities

• Partner with teams to identify model risks.
• Leverage technologies to analyze data.
• Build machine learning models to improve current models.
• Present insights to executives.
• Validate models across various business domains.

Skills

Data analysis

Machine learning

Open source programming

Statistical modeling

Education

Bachelor's Degree in a quantitative field

Master's Degree in a quantitative field

PhD in a quantitative field

Tools

Python

AWS

SQL

Job description

Manager, Data Scientist

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

In Capital One’s Model Risk Office, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can’t prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We learn from past mistakes, and develop increasingly powerful techniques to avoid their repetition.

Role Description

In this role, you will:

• Partner with a cross‑functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models
• Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
• Build machine learning models to challenge "champion models" that are deployed in production today
• Contribute to the model governance framework for the next generation of machine learning models
• Flex your interpersonal skills to present how model risks could impact the business to executives
• Validate a wide variety of models across multiple business domains within our Enterprise Services division

The Ideal Candidate

• Innovative. 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.
• Creative. 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, and you’re not afraid to learn about different aspects of Capital One’s businesses.
• Technical. 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.

Basic Qualifications

• Currently has, or is 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
• At least 4 years’ experience building or validating models related to fraud detection, digital marketing, cybersecurity, or sensitive data detection.

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full‑time annual salaries for this role are listed below, by location. Salaries are based on the candidate’s location and the annualized salary will be reflected in the offer letter.

McLean, VA: $197,300 - $225,100

Richmond, VA: $179,400 - $204,700

This role is eligible for performance‑based incentive compensation, which may include cash bonuses and/or long‑term incentives.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total wellbeing.

Capital One is an equal‑opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws.