At Capital One 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 will 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
At Capital One India, we are at the cutting edge of solving some of the fundamental business problems using advanced data methodologies, statistics, and machine learning algorithms. The Model Risk Management team acts as a critical line of defense, identifying and mitigating risks associated with the bank's most sophisticated decision-making systems. We combine statistics, software engineering, and business expertise to drive the best outcomes for the Enterprise, ensuring that every model from deposits pricing to fraud detection is robust and reliable.We understand that we cannot prepare for tomorrow by focusing only on today; therefore, we invest heavily in new skills and building better tools to govern emerging technologies like Generative AI. Our team thrives on a rigorous challenge culture to develop increasingly powerful validation techniques that ensure model integrity and regulatory compliance.
About the Role
As a Principal Associate in Retail Banking Model Risk Management team, you will provide independent oversight and technical challenge for state-of-the-art models, focusing on the high-stakes domains of Fraud, Deposits, and Generative AI. General responsibilities include but are not limited to:
Independent Validation and Challenge: Assess and challenge state-of-the-art decision-making models, including ML and Gen AI, to internal stakeholders and regulatory partners.
Cross-Functional Governance: Partner cross-functionally with model developers, business analysts, and tech teams to enable the safe capturing of risky behavior while influencing broader business strategies.
Innovation in Advanced Modeling: Demonstrate ability to explore and quickly grasp new technologies to progress varied initiatives. Collaborate with Quants and Data Scientists to drive innovation and research in advanced modeling space, leading to high-performing benchmark model development.
Technical Tool Building: Build data products and custom software tools for automated model performance evaluation, back-testing, and data exploration using open-source and cloud platforms.
Advanced Analytics: Utilize your statistical toolset to mine complex, voluminous data sources, providing meaningful insights on business strategies through rigorous model assessment.
Technical Communication: Communicate complex technical subject matter and research results clearly and concisely to non-specialist audiences and senior management.
Regulatory Diplomacy: Flex your interpersonal skills to defend or challenge model methodologies with developers, auditors, and regulators, ensuring all solutions meet stringent industry standards.
The ideal candidate is:
Inquisitive. 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.
ML/Statistically minded. You’ve built models, validated them, and back tested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, time series, and deep learning.
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.
Basic Qualifications:
Bachelor’s degree in statistics, math, engineering, economics, econometrics, financial engineering, finance, or operations research with a quantitative focus.
At least 4 years of experience in data analytics.
At least 3 years of experience in Python or R.
Preferred Skills:
Proficiency in key econometric and statistical techniques (such as predictive modeling, logistic regression, panel data models, decision trees, machine learning methods)
4+ years of experience model development or validation
4+ years of experience in R or Python for large scale data analysis
4+ years of experience with relational databases and SQL
Strong analytical skills with high attention to detail and accuracy
Excellent written and verbal communication skills
Experience in financial services industry
Experience in Fraud Domain and Generative AI
At this time, Capital One will not sponsor a new applicant for employment authorization for this position.
No agencies please. 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.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).