Manager, Data Scientist - Velocity Black (Remote-Eligible)

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

Velocity Black by Capital One harnesses the power of artificial intelligence, the warmth of human experts and the convenience of the latest interfaces to help high-performance people actualize the full potential of their lives. It's concierge, reimagined for the digital age.

By harnessing 24/7 chat, AI, and mobile payments, we help our customers do more and be more in the digital age. From access to the hottest restaurants to guaranteed upgrades at the world’s finest resorts. Make a custom request through the app and you will be chatting to our team within 1 minute, 24/7/365.

Velocity Black is on a mission to leverage technology to improve our operational efficacy and provide an extraordinary member experience. The Velocity Black AI and ML team is building the models that help provide personalized recommendations for our members. Our solutions are both:

• Reactive: Match member requests to the best possible options based on their stated request parameters, preferences, and historical behavior, as well as incorporating the expertise of our human agents.
• Proactive: Surface tailored, curated recommendations in-app, where content is filtered and personalized to each individual member, anticipating their needs and inspiring new booking experiences with us.

The team is a combination of product managers, engineers, business analysts, and data scientists working in tandem to building AI/ML solutions from the ground up to help scale and improve our Velocity Black services.

We are looking for someone passionate about digital servicing, customer experience, and personalization to work on our Velocity Black Concierge product.

Role Description

In this role, you will:

• Lead the design, development, and maintenance of personalization and recommendation models.
• Apply modern AI/ML methods (e.g. collaborative filtering, ensemble retrievers, embeddings, neural networks, LLM as a judge, etc.) to optimize and elevate member experiences
• Collaborate with product/business and engineering to integrate models into our platform, including model registration and ongoing measurement.
• Develop evaluation frameworks to monitor performance, bias, and accuracy of recommendations.
• Champion data-driven decision making across the team.

The Ideal Candidate is:

• Customer first. You love the process of analyzing and creating, and you care about the user of the systems you create. You know at the end of the day it’s about providing tooling to support our agents and enhancements to delight our customers.
• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and brainstorming various technical methods and designs to find the best solutions. You’re not afraid to share a new idea.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo to advance us to the most cutting edge methods. You’re passionate about talent development for your own team and beyond.
• Technical. You’re comfortable with all things model development, including from pulling together model input data from various sources to deciding on the appropriate methodology to helping to implement use cases within thoughtful architecture designs. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

• Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
  • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
  • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics
  • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics
• At least 1 years of experience leveraging open source programming languages for large scale data analysis
• At least 1 year of experience working with machine learning
• At least 1 year of experience utilizing relational databases

Preferred Qualifications:

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
• Strong proficiency in Python and SQL for large scale data analysis
• At least 1 year of experience preparing and transforming large, messy, or sparse datasets for modeling
• At least 1 year of experience designing, training, and deploying large-scale models in production
• At least 1 year of experience in model lifecycle management and ML ops practices (monitoring, feature stores, retraining, experimentation, and A/B testing)
• At least 1 year of experience collaborating cross-functionally with product and engineering to translate business problems into ML solutions
• Familiarity with sophisticated ML approaches to personalization models or recommendation systems
• Demonstrated ability to influence stakeholders and lead technical strategy