Capital One - Chicago, IL
posted 5 months ago
Data is at the center of everything we do at Capital One. As a Principal Data Scientist in the Model Risk Office, you will play a crucial role in defending the company against model failures and finding innovative ways to enhance decision-making through advanced modeling techniques. This position is not just about analyzing data; it's about leveraging your expertise in statistics, software engineering, and business acumen to drive optimal outcomes in Risk Management and across the Enterprise. You will be part of a team that is committed to investing in the future by building better tools, developing new skills, and maintaining a network of trusted partners. We learn from past mistakes and continuously develop powerful techniques to avoid their repetition. In this role, you will partner with a cross-functional team of data scientists, software engineers, and product managers to deliver products that customers love. You will utilize a broad stack of technologies, including Python, Conda, AWS, H2O, and Spark, to uncover insights from vast amounts of numeric and textual data. Your responsibilities will include building machine learning models through all phases of development, from design to training, evaluation, validation, and implementation. You will also need to effectively communicate the complexity of your work into tangible business goals, ensuring that the customer remains at the forefront of your efforts. The ideal candidate for this position is someone who is customer-focused, innovative, technical, and statistically-minded. You should have a passion for analyzing and creating solutions that prioritize the needs of our customers. You will be expected to stay current on emerging technologies and seek opportunities to apply state-of-the-art methods in your work. Your technical skills should include experience with open-source programming languages and cloud computing platforms, as well as a solid understanding of statistical modeling and machine learning techniques.