VP, Head of Data Science

About Us

Capital Bank N.A. is headquartered in Maryland and has been serving our communities since 1999. We stand as a publicly traded company (NASDAQ: CBNK) with over $3 billion in assets. We offer commercial and consumer banking services to clients primarily in Maryland, DC, and Northern Virginia, alongside two nation‑wide lending brands;
Capital Bank Home Loans and Open Sky, a credit card division that offers and services credit cards across all states. Our personalized approach to banking, paired with cutting‑edge technology solutions and a comprehensive suite of products and services, fuels our growth, and enables us to support our customers at every stage in their financial journey.

At Open Sky, we believe that everyone has the right to access credit and achieve their financial goals. We have helped over 1.2 million customers get started and continue their path to realizing their financial goals. And we want to help and grow with our customers even more – by expanding our offerings to support them in their credit journey, and providing compelling products and digital solutions for education, advice, and financial services.

Open Sky is a high‑growth, data‑driven, dynamic, and entrepreneurial environment where you are limited only by your imagination. You'll work with some of the brightest and most passionate minds in the Fin Tech industry, and from day one, start having a real impact on consumers' lives and financial goals.

As the Head of Data Science for Open Sky, you will lead the strategy, development, and execution of advanced analytics and modeling solutions that power our credit card lending business. This is a unique opportunity to build credit risk and fraud models from the ground up as we launch a new unsecured card product. You will shape the future of our data science capabilities, ensure robust model governance, and leverage cutting‑edge machine learning techniques to drive business growth and manage risk.

This is a hands‑on leadership role with significant influence and the opportunity to scale the team and its impact over time.

• Set a bold vision and roadmap for data science, aligning with business objectives and growth priorities
• Lead the development of new credit risk and fraud models from scratch to support the launch of our unsecured card business
• Manage model delivery efforts, ensuring results are delivered on time and with quality
• Own the model lifecycle— from design and development to deployment, monitoring, and continuous improvement
• Influence executive decision‑making by presenting insights and recommendations in a clear, compelling manner
• Oversee model suite, monitoring for performance and identifying opportunities for improvement
• Ensure model governance and compliance, including documentation, validation, and adherence to regulatory standards
• Lead and mentor a team of data scientists and analysts, providing technical guidance, career development, and performance feedback
• Foster cross‑functional collaboration with product, technology, and data teams to ensure seamless integration of data science solutions
• Stay ahead of industry trends and emerging technologies to keep the team at the cutting edge

• Bachelor's degree in a quantitative field (e.g., Statistics, Data Science, Applied Mathematics)
• Advanced degree in a quantitative field (e.g., Statistics, Data Science, Applied Mathematics) preferred
• 10+ years of experience in data science, with a strong track record of building and deploying predictive models in financial services
• 2–5+ years of leadership experience building and scaling data science teams
• Proven track record of delivering measurable business impact through data‑driven solutions
• Deep understanding of credit risk modeling, fraud detection, and regulatory requirements
• Have an ownership mindset and exceptional results focus and project management skills
• Relentless persistence in solving problems
• Strong executive presence and communication skills: ability to clearly and effectively communicate complex analytical insights to both technical and non‑technical audiences

• Advanced SQL
• Adv…