Bangalore, In, India · 13 days ago
You will build and validate statistical and machine learning models, build custom data tools, and communicate results to business, validation and regulatory audiences as part of Capital One's Model Risk Management team in India.
Voyager (94001), India, Bangalore, Karnātaka Senior Associate, Data Science 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. Today, we are a high-tech company, a scientific laboratory, and a nationally recognized brand all in one impacting over 65 million customer accounts. Still founder-led by Chairman and CEO Richard Fairbank, we dare to dream, disrupt, and deliver a better way for our customers, the financial industry and for each other. As a Data Scientist, you will be part of a team that is leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies to unlock the big opportunities that help drive efficiency and improve customer experience. And you will do it all in a collaborative environment that values your insight, encourages you to take on new responsibility, promotes continuous learning, and rewards innovation. 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. Role Description General responsibilities include but are not limited to: Partner cross-functionally with teams throughout the enterprise including Product and Tech to deliver solutions. You will enhance your technical and analytical skills, while also working with leaders to influence business strategies. Collaborate with Quants, Data Scientists, Data analysts, Business analysts and risk managers to drive innovation, and shape strategic initiatives. Utilize data to drive real-world impact and thrive in a collaborative, forward-thinking environment. Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners. Build upon your existing machine learning and statistical toolset - both by learning new technologies and by building custom software tools for data exploration, model performance evaluation, and more. Use Open Source/Digital technologies to mine complex, voluminous, and different varieties of data sources and platforms. Build well-managed data products, data solutions, tools, and capabilities to enable self-service frameworks for data consumers. Demonstrate ability to explore and quickly grasp new technologies to progress varied initiatives. Drive analysis that provides meaningful insights on business strategies. 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. Flex your interpersonal skills to defend the model with validators, auditors and regulators. 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 are 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. Quantitative and ML/Statistically-minded: You’ve built models, validated them, and worked with them. Thrive in a dynamic and fast-paced environment: You are comfortable with ambiguity and enjoy cutting through distractions to discern priorities and create structure where none exists. You understand the big picture but are also able to execute with close attention to detail. 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, finance or operations research with a quantitative focus. At least 2 years of experience in data analytics. At least 1 year’s experience in Python or R. Preferred Qualifications: 2+ years of experience in model development or validation. 2+ years of experience in R or Python for large scale data analysis. 2+ 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 the financial services industry. Proficiency in key econometric and statistical techniques, model design, development and deployment experience Experience in evaluating and working with emerging technologies and algorithms. 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). At Capital One, we’re building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit.
Posted Oct 26, 2026
