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.

• 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