Senior Manager, Data Science - Model and Script Enhancement (MASE) Compliance
Capital OneAbout the role
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.
In Capital One’s Compliance and Ethics Organization, we support the business in managing regulatory compliance risk through advice and effective challenge. Model and Script Enhancement (MASE) Compliance was established with a specific focus on assessing compliance risk in models and scripts and advising the business on how to manage the identified risk.
Role Description
In this role, you will:
Own and drive the assessment process over computer code (script) reviews - Code Design Intent Review (CoDIR). CoDIR is designed to evaluate the regulatory requirements the script is intended to effectuate and whether the script, as designed, meets that regulatory intent and to report the result of the assessment to the script owner.
Own and execute the methodology for identifying high compliance risk scripts
Monitor the Script Governance Inventory to identify high compliance risk scripts as candidates for CoDIR review
Prepare CODIR assessments and report results.
Execute CODIRs on scripts identified through the model risk assessment process; referred by the Compliance testing program or other channels
Identify opportunities to leverage GenAI or other capabilities to improve processes and automation
The Ideal Candidate is:
Innovative. Continually researches and evaluates emerging technologies. Stays current on published state-of-the-art methods, technologies, and applications and seeks out opportunities to apply them.
A leader. Challenges conventional thinking and works with stakeholders to identify and improve the status quo.
Statistically-minded. Has built models and validated them; familiar with coding logic and languages
Risk Management focused. Understands the importance and role of compliance risk management
Team Player. Can successfully build and manage relationships across multiple groups
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 7 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 5 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 2 years of experience performing data analytics
At least 2 years of experience leveraging open source programming languages for large scale data analysis
At least 2 years of experience working with machine learning
At least 2 years of experience utilizing relational databases
Preferred Qualifications:
At least 5 years’ experience in Python, SQL and Java
At least 5 years’ experience with machine learning
Banking regulatory compliance experience
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. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
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