Senior Data Scientist
Role overview
Q2’s Relationship Pricing platform, used by thousands of commercial bankers across hundreds of banks of all sizes, empowers bankers to win better deals and grow stronger relationships. As a Senior Data Scientist on the team, you will work closely with cross-functional teams to lead large complex data science projects from exploration to deployment. You will help build and operate production systems that power the analytics and insights uncovered from one of the world’s largest commercial banking datasets and play an active role in shaping the product roadmap by identifying where data science and AI can create highest business and user value.
Responsibilities
- check_circle Explore and engineer features from large, complex commercial banking datasets including loan pricing, relationship profitability, and deal performance data
- check_circle Design and prototype machine learning models — including pricing recommendation, deal win likelihood, and anomaly detection — and see them through to production deployment
- check_circle Build and evaluate LLM-powered features including RAG pipelines, prompt engineering, and embedding-based retrieval over banking data
- check_circle Partner with product and business stakeholders to translate commercial banking problems into data science solutions, and contribute to roadmap prioritization
- check_circle Collaborate with engineering teams to deploy and maintain production-grade models and analytics systems
- check_circle Mentor junior team members and contribute to best practices in modeling, experimentation, and responsible AI
- check_circle Communicate findings and model insights through compelling visualizations and presentations to both technical and non-technical audiences
Basic qualifications
- 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).
Preferred qualifications
- Familiarity with vector databases and embedding-based retrieval
- Experience with cloud platforms (AWS, GCP, or Azure)
- Experience with BI tooling (PowerBI or equivalent)
- Experience with financial services, banking or fintech – commercial banking familiarity strongly preferred
Benefits
- check_circle Hybrid Work Opportunities
- check_circle Flexible Time Off
- check_circle Career Development & Mentoring Programs
- check_circle Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents
- check_circle Community Volunteering & Company Philanthropy Programs
- check_circle Employee Peer Recognition Programs – “You Earned it”
About the company
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 simple: build strong and diverse communities through innovative financial technology—and we do that by empowering our people to help create success for our customers.
Tags & Focus Areas
About Q2ebanking
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