Senior Data Scientist

Q2

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Cary, NC
Posted
28 days ago
Freshness
Confirmed live yesterday
Closes
Nov 30, 2026

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Salary context

How this pay compares to similar roles

Similar $158k
$91k most similar roles pay here $224k

This listing doesn't post a salary. Most similar roles pay $126,800–$189,982.

Based on 240 similar postings.

Employer

About Q2

Q2 Holdings is a cloud-based banking software company providing digital banking solutions to banks, credit unions, and alternative financial companies, including consumer and business banking platforms. Industry: Financial Technology & Digital Banking

Q2 currently has 31 open roles on FindRole.

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At a glance

TL;DR · Senior Data Scientist

As a Senior Data Scientist on the Relationship Pricing team, you will lead complex data science projects from initial exploration through production deployment. You will be responsible for building and operating production systems that derive insights from large commercial banking datasets, including loan pricing and deal performance. Your daily work involves engineering features, prototyping machine learning models for pricing recommendations and anomaly detection, and developing LLM-powered features using RAG pipelines, prompt engineering, and embedding-based retrieval. You will collaborate with cross-functional teams to translate business problems into technical solutions while mentoring junior members. The role requires proficiency in Python or R, SQL, and various machine learning libraries. Preferred skills include experience with vector databases, cloud platforms like AWS, GCP, or Azure, and BI tools like PowerBI within the financial services or fintech domain.

What does a Data Scientist earn?

Median $162025 from 276 postings across 61 companies.

See salary data

What you'll do

  • Engineer features from large, complex commercial banking datasets including loan pricing and deal performance.
  • Design and prototype machine learning models for pricing recommendations, win likelihood, and anomaly detection.
  • Build and evaluate LLM-powered features using RAG pipelines, prompt engineering, and embedding-based retrieval.
  • Translate complex commercial banking problems into actionable data science solutions for product stakeholders.
  • Deploy and maintain production-grade models and analytics systems in collaboration with engineering teams.
  • Mentor junior team members on modeling best practices, experimentation, and responsible AI.
  • Communicate model insights and findings through visualizations and presentations to technical and non-technical audiences.

What we're looking for

  • A Bachelor's degree in Data Science, Computer Science, Statistics, or a related field.
  • An advanced degree with at least 6 years of experience.
  • At least 8 years of related experience for candidates with a Bachelor's degree.
  • Strong proficiency in Python or R, SQL, and machine learning libraries.
  • Hands-on experience with large language models, including prompt engineering, RAG, and evaluation frameworks.
  • Proven ability to lead end-to-end data science projects from discovery through production.
  • Experience writing clean code and using version control systems like Git.
  • Authorization to work for any employer in the U.S.

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