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Voyager (94001), India, Bangalore, Karnataka
Senior Associate, Business Analysis
About the Company
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 an Analyst 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.
Team Description
At DataLabs 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.
In the DataLabs Model Risk Management team, 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 also
understand that we can't prepare for tomorrow by focusing 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 cross-functionally with data scientists, quantitative analysts, business analysts, software engineers, and project managers to manage the risk and uncertainty inherent in statistical and
machine learning models in order to lead Capital One to the best decisions, not just avoid the worst ones.• Build and validate statistical and machine learning models through all phases of development, from design through training, evaluation and implementation• Develop new ways of identifying weak spots in model predictions earlier and with more confidence than the best available methods• Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners• Leverage a broad stack of technologies - Python, R, Conda, AWS, and more - to reveal the insights hidden within huge volumes of data• 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• 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 translate the complexity of your work into tangible business goals, and challenge model developers to advance their modeling, data, and analytic capabilities
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.• 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, 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:• Degree in statistics, math, engineering, economics, econometrics, financial engineering, finance, or operations research with a quantitative emphasis preferred• Atleast 2 years relevant work experience• 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)• Atleast 2 years of experience model development or validation• Atleast 2 years of experience in R or Python for large scale data analysis• Atleast 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
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).
Senior Associate, Business Analysis
About the Company
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 an Analyst 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.
Team Description
At DataLabs 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.
In the DataLabs Model Risk Management team, 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 also
understand that we can't prepare for tomorrow by focusing 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 cross-functionally with data scientists, quantitative analysts, business analysts, software engineers, and project managers to manage the risk and uncertainty inherent in statistical and
machine learning models in order to lead Capital One to the best decisions, not just avoid the worst ones.• Build and validate statistical and machine learning models through all phases of development, from design through training, evaluation and implementation• Develop new ways of identifying weak spots in model predictions earlier and with more confidence than the best available methods• Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners• Leverage a broad stack of technologies - Python, R, Conda, AWS, and more - to reveal the insights hidden within huge volumes of data• 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• 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 translate the complexity of your work into tangible business goals, and challenge model developers to advance their modeling, data, and analytic capabilities
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.• 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, 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:• Degree in statistics, math, engineering, economics, econometrics, financial engineering, finance, or operations research with a quantitative emphasis preferred• Atleast 2 years relevant work experience• 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)• Atleast 2 years of experience model development or validation• Atleast 2 years of experience in R or Python for large scale data analysis• Atleast 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
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).
What you need to know about the Chennai Tech Scene
To locals, it's no secret that South India is leading the charge in big data infrastructure. While the environmental impact of data centers has long been a concern, emerging hubs like Chennai are favored by companies seeking ready access to renewable energy resources, which provide more sustainable and cost-effective solutions. As a result, Chennai, along with neighboring Bengaluru and Hyderabad, is poised for significant growth, with a projected 65 percent increase in data center capacity over the next decade.
