Principal Associate, Data Science - Model Risk Office

Capital One; Plano (TX); On-site; USD 147,000 - 168,000; Full time

Job summary

Capital One is seeking a Data Scientist to join the Model Risk Office, tackling model risk across multiple domains using Python, AWS, and a broad tech stack. You will lead data science teams, validate diverse models, and present risks to executives as part of governance for next-generation solutions.

The role emphasizes collaboration with data scientists, engineers, and product managers, along with strong focus on statistical methods, backtesting, and time series analysis to inform critical risk

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
• Bachelor's Degree in a quantitative field plus 5 years of experience performing data analytics
• Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of experience performing data analytics
• PhD in a quantitative field

Responsibilities

• 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, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
• Lead teams of data scientists who build machine learning models to challenge current champion models that are deployed in production and contribute to the model governance framework for the next generation of models
• Lead validation of a wide variety of models across multiple business domains and flex your interpersonal skills to present how identified model risks could impact the business to executives

Skills

Statistical modeling

Data analysis

Machine learning

Leadership

Education

Bachelor's degree in quantitative field

Master's degree in quantitative field or MBA with quant concentration

PhD in quantitative field

Tools

Python

Conda

AWS

H2O

Spark

SQL

Job description

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.

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 just 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, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
• Lead teams of data scientists who build machine learning models to challenge current champion models that are deployed in production and contribute to the model governance framework for the next generation of models
• Lead validation of a wide variety of models across multiple business domains and flex your interpersonal skills to present how identified model risks could impact the business to executives.

The Ideal Candidate is:

• 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.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
• 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.

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 5 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 3 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)

Preferred Qualifications:

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
• At least 1 year of experience working with AWS
• At least 3 years’ experience in Python, Scala, or R
• At least 3 years’ experience with machine learning
• At least 3 years’ experience with SQL

Chicago, IL: $147,100 - $167,900 for Princ Associate, Data Science
McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science
New York, NY: $176,500 - $201,400 for Princ Associate, Data Science
Plano, TX: $147,100 - $167,900 for Princ Associate, Data Science
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). 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. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

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 regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.