Principal Associate, Data Scientist - Mainstreet Acquisitions
AI summary of the role
This Principal Associate Data Scientist role on the Valuations team focuses on developing and deploying credit underwriting models for Mainstreet Acquisitions.
What you’ll do
- Conduct model development, experimenting with various statistical methodologies to improve model performance
- Leverage alternative data sources along with various feature selection and engineering techniques to enhance in market models
- Develop next-gen credit underwriting models
- Partner with key stakeholders across the organization to establish standards for new modeling approaches
What you’ll bring
- Bachelor's degree in a quantitative field plus 5 years data analytics experience, or Master's plus 3 years, or PhD
- At least 3 years experience in Python, Scala, or R
- At least 3 years experience with machine learning
- At least 3 years experience with SQL
Technologies
Python · Conda · AWS · Spark · Scala · R · SQL · machine learning · statistical modeling · deep learning
Source and classification
Internal deployment & tooling · Evidence for this classification:
focused on the development, deployment, model governance, and risk management of valuations model in credit underwriting. Our mission is to bring real-time, personalized offers to our customers - via innovation and optimization in our valuations modeling system. We work with partners from across the enterprise to build data and modeling products that enable best in class credit analysis and customer-facing decisioning. Underwriting innovation is a key source of Capital One’s competitive advantage - it is in our DNA. Our team continues to push that competitive edge through the use of new data and advanced modeling techniques. Building the capabilities that the enterprise needs is a challenging long term project; the prize is big and there are plenty of opportunities to deliver value on the way. To bring our vision to life, as a model developer and data scientist, you can expect to:
More from the job description
Principal Associate, Data Scientist - Mainstreet Acquisitions 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’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 Valuations team is a multi-disciplinary team focused on the development, deployment, model governance, and risk management of valuations model in credit underwriting. Our mission is to bring real-time, personalized offers to our customers - via innovation and optimization in our valuations modeling system. We work with partners from across the enterprise to build data and modeling products that enable best in class credit analysis and customer-facing decisioning. Underwriting innovation is a key source of Capital One’s competitive advantage - [... source excerpt omitted ...] approaches to improve our lending decisions. Our team’s work is both intellectually demanding and highly collaborative. As part of an enterprise team delivering new capabilities, you will be working across: LOB underwriting teams, various DS/DA teams, enterprise platform teams, enterprise data team, tech teams, legal and compliance teams, consumer credit risk management, model risk office, and enterprise data risk management. Great team culture is profoundly important to us: we want everyone to feel they are doing meaningful and enjoyable work; we are informal and indifferent to hierarchy; we actively encourage new ideas and new ways of doing things; we respect each other’s per [... source excerpt omitted ...] and preferences. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but
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