Senior Data Scientist

About Us

Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the U.S. and internationally. Our mission is to build strong and diverse communities through innovative financial technology by empowering our people to help create success for our customers.

We celebrate our employees through initiatives like the “Circle of Awesomeness” award ceremony and an annual day of employee celebration. We invest in growth and development via learning opportunities, mentorship programs, internal mobility, and leadership relationships. We foster trust and collaboration through events like our annual Dodgeball for Charity at Q2 Stadium in Austin, where local companies and community organizations come together to raise money and awareness.

About the Role

As a Senior Data Scientist on Q2’s Relationship Pricing team, you will lead large, complex data science projects from exploration to deployment. You’ll work with cross-functional teams to build and operate production systems that power analytics and insights from one of the world’s largest commercial banking datasets. Your role will include shaping the product roadmap by identifying high-value opportunities for data science and AI.

A Typical Day

• Explore and engineer features from large, complex commercial banking datasets, including loan pricing, relationship profitability, and deal performance data.
• Design and prototype machine learning models—such as pricing recommendations, deal win likelihood, and anomaly detection—and deploy them to production.
• Build and evaluate LLM-powered features, including RAG pipelines, prompt engineering, and embedding-based retrieval over banking data.
• Partner with product and business stakeholders to translate commercial banking problems into data science solutions and contribute to roadmap prioritization.
• Collaborate with engineering teams to deploy and maintain production-grade models and analytics systems.
• Mentor junior team members and contribute to best practices in modeling, experimentation, and responsible AI.
• Communicate findings and model insights through compelling visualizations and presentations to technical and non-technical audiences.

Requirements

• Typically requires a Bachelor’s degree in Data Science, Computer Science, Statistics, or a relevant field and 8 years of related experience; or an advanced degree with 6+ years of experience; or equivalent related work experience.
• Strong proficiency in Python or R, SQL, and machine learning libraries.
• Hands-on experience with large language models, including prompt engineering, RAG, and LLM evaluation frameworks.
• Proven ability to lead end-to-end data science projects from discovery through production.
• Experience writing clean, maintainable code and using version control (e.g., Git).
• Fluent written and oral communication in English.
• Authorized to work for any employer in the U.S. (no visa sponsorship available at this time).

Preferred Experience

• Familiarity with vector databases and embedding-based retrieval.
• Experience with cloud platforms (AWS, GCP, or Azure).
• Experience with BI tooling (PowerBI or equivalent).
• Experience in financial services, banking, or fintech—commercial banking familiarity strongly preferred.

Benefits

• Hybrid work opportunities.
• Flexible time off.
• Career development and mentoring programs.
• Competitive health insurance offerings and generous paid parental leave for eligible new parents.
• Community volunteering and company philanthropy programs.
• Employee peer recognition programs (“You Earned It”).
• Wellness resources for physical, mental, and professional well-being.

Q2 employees are encouraged to give back through volunteer work and nonprofit support via our Spark Program.