Manager, Data Science - Model Risk Office

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

Benefits offered by this job

Comprehensive health benefits

Performance-based incentives

Inclusive workplace environment

Job summary

Capital One is looking for a Manager, Data Science for its Model Risk Office. You will validate payment network models, including fraud and Anti-Money Laundering (AML) risks, utilizing advanced statistical techniques and machine learning. Strong communication skills are essential for engaging stakeholders from various backgrounds.

The ideal candidate has a quantitative degree with significant experience in data analytics and machine learning. This role offers a competitive salary and benefits package.

Qualifications

• 6 years of experience performing data analytics with Bachelor's degree.
• 4 years with Master's degree or MBA in quantitative field.
• 1 year leveraging open-source programming for data analysis.
• 1 year working with machine learning.

Responsibilities

• Perform independent model validations for payment network models.
• Validate statistical and machine learning models.
• Communicate technical subject matter clearly.
• Develop high quality documentation.

Skills

Data analysis

Machine learning

Statistical modeling

Communication skills

Education

Bachelor's Degree in a quantitative field

Master's Degree in a quantitative field

PhD in a quantitative field

Tools

Python

AWS

Open-source languages

Relational databases

Job description

Manager, Data Science - Model Risk Office

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.

Capital One is selectively recruiting for a Manager for a Model Validation team. The individual would report to the Model Risk Office and work closely with the business groups. This position is responsible for validating payment network business models, including fraud risk, Anti‑Money Laundering (AML), Counterparty risk, and financial models. Strong communication skills are essential to effectively engage with a diverse group of stakeholders, irrespective of their technical background.

Role Description

• Perform independent model validations for payment network models, including fraud, AML, counterparty and financial models in accordance with regulatory guidance SR 11‑7 and internal model risk policy and standards.
• Validate fraud and AML modeling approaches, including:
• Rule‑based systems and thresholds
• Statistical models
• Machine learning models, (e.g., Gradient Boosting, Random Forecast)
• Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools
• Understand relevant business processes and portfolios associated with model use
• Understand technical issues in econometric, statistical, and machine learning modeling and apply these skills toward developing models and assessing model risks and opportunities
• Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication; prepare presentations of complex technical concepts and research results to non‑specialist audiences and senior management
• Maintain the efficiency and accuracy of our models through continuous improvement and application of best practices
• Develop and maintain high quality and transparent documentation
• Leverage the latest open‑source technologies and tools to identify areas of opportunity in our existing framework

The Ideal Candidate is:

• Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
• 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.
• 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

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

McLean, VA: $197,300 - $225,100 for Mgr, Data Science

Riverwoods, IL: $179,400 - $204,700 for Mgr, Data Science

This role is also eligible to earn performance based incentive compensation, which may include cash bonus and/or long term incentives. Incentives could be discretionary or non‑discretionary depending on the plan.

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

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.