Senior Data Scientist

Q2ebanking; Cary (NC); On-site; USD 130,000 - 170,000; Full time

Benefits offered by this job

Hybrid work

Flexible time off

Career development & mentoring

Health insurance

Parental leave

Volunteer programs

Peer recognition

Job summary

Q2ebanking in Cary, NC is seeking a Senior Data Scientist to lead large, complex data science efforts within its Relationship Pricing platform. You will own the full analytics lifecycle from discovery to production deployment, collaborating with product and engineering teams.

You will engineer features from banking datasets, design pricing models, and build LLM-powered capabilities, while mentoring junior teammates and presenting insights to both technical and non-technical audiences.

Qualifications

• Bachelor’s degree in Data Science, CS, Statistics, or related field; 8+ years experience, or advanced degree with 6+ years, or equivalent work
• Strong Python or R, SQL, and ML libraries proficiency
• Hands-on with large language models, prompt engineering, RAG, and evaluation frameworks
• Proven ability to lead end-to-end data science projects from discovery through production
• Experience writing clean, maintainable code and using Git for version control

Responsibilities

• Explore and engineer features from large, complex banking datasets (loan pricing, profitability, deal performance)
• Design, prototype, and deploy ML models (pricing recommendations, deal win likelihood, anomaly detection)
• Build and evaluate LLM-powered capabilities, including RAG pipelines and embedding-based retrieval
• Collaborate with product/engineering to translate use cases into DS solutions and roadmap
• Mentor junior team members and promote modeling best practices and responsible AI
• Present findings with clear visualizations to technical and non-technical audiences

Skills

Python

R

SQL

Machine learning libraries

LLMs / prompt engineering / RAG

Git

End-to-end DS projects

Education

Bachelor's degree

Advanced degree (6+ years)

Tools

PowerBI

Git

AWS

GCP

Azure

Job description

Q2ebanking is seeking a Senior Data Scientist to lead large, complex data science efforts within its Relationship Pricing platform. This hybrid role in Cary, NC spans the full lifecycle of analytics and machine learning work, from early exploration to production deployment, while partnering closely with product and engineering teams.

What you’ll do

• Explore and engineer features using large, complex commercial banking datasets, including loan pricing, relationship profitability, and deal performance data
• Design, prototype, and operationalize machine learning models such as pricing recommendation, deal win likelihood, and anomaly detection
• Build and evaluate LLM-powered capabilities, including RAG pipelines, prompt engineering, and embedding-based retrieval over banking data
• Work with product and business stakeholders to translate commercial banking use cases into data science solutions and help inform 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
• Present findings and model insights through clear visualizations and presentations for both technical and non-technical audiences

What you bring

• Typically requires a Bachelor’s degree in Data Science, Computer Science, Statistics, or a relevant field, plus 8 years of related experience; alternatively, an advanced degree with 6+ years, 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)

Tools and technologies you may use

• Python, R, SQL, machine learning libraries
• LLM, prompt engineering, RAG, LLM evaluation frameworks, embedding-based retrieval
• Vector databases
• AWS, GCP, or Azure
• PowerBI, Git

Preferred experience

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

Benefits

• Hybrid work opportunities
• Flexible time off
• Career development & mentoring programs
• Health & wellness benefits, including competitive health insurance and generous paid parental leave for eligible new parents
• Community volunteering & company philanthropy programs
• Employee peer recognition programs (You Earned it)