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Fintech Data Science Jobs in Raleigh, NC (NOW HIRING)

Senior Data Scientist

Cary, NC · On-site

$140 - $200/hr

Proven ability to lead end-to-end data science projects from discovery through production ... Experience with financial services, banking or fintech - commercial banking familiarity strongly ...

New

Proven ability to lead end-to-end data science projects from discovery through production ... Experience with financial services, banking or fintech - commercial banking familiarity strongly ...

Proven ability to lead end-to-end data science projects from discovery through production ... Experience with financial services, banking or fintech - commercial banking familiarity strongly ...

... leverage data to strengthen their portfolio. Abrigo is seeking a Senior IT Audit & Assurance ... Bachelor's degree in Information Systems, Accounting, Computer Science, or related discipline ...

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Showing results 1-20

Fintech Data Science information

See Raleigh, NC salary details

$36.5K

$119.3K

$191K

How much do fintech data science jobs pay per year?

As of Aug 10, 2026, the average yearly pay for fintech data science in Raleigh, NC is $119,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $132,200.00 per year, depending on experience, location, and employer.

What is a fintech data scientist?

A Fintech Data Scientist is a professional who uses data analysis, machine learning, and statistical techniques to solve problems and create value within the financial technology (fintech) industry. They work with large amounts of financial data to develop predictive models, detect fraud, assess risk, and optimize financial products or services. Their expertise combines knowledge of finance, programming, and advanced analytics to help fintech companies make data-driven decisions and innovate in areas such as payments, lending, and investment. Fintech Data Scientists often collaborate with engineers, product managers, and business stakeholders to deliver actionable insights that drive business growth.

How do fintech data scientists typically collaborate with product and engineering teams to develop new financial products?

In fintech, data scientists often work closely with product managers and engineering teams throughout the lifecycle of a financial product. They analyze user data and market trends to provide actionable insights during the product design phase, and collaborate with engineers to implement machine learning models into the product infrastructure. Regular cross-functional meetings and agile workflows are common, allowing data scientists to iterate on models based on feedback and evolving requirements. This collaborative environment ensures that data-driven solutions are robust, scalable, and aligned with business goals.

What are the key skills and qualifications needed to thrive as a fintech data scientist?

To thrive as a Fintech Data Scientist, you need a strong background in statistics, machine learning, and programming (often with a degree in computer science, mathematics, or a related field). Familiarity with tools such as Python, R, SQL, cloud computing platforms, and experience with financial data modeling or relevant certifications are typically required. Strong problem-solving skills, attention to detail, and effective communication are important soft skills that set top professionals apart. These skills and qualities are vital for extracting actionable insights from complex financial data, driving innovation, and ensuring regulatory compliance in the fast-evolving fintech industry.

What is the difference between Fintech Data Science vs Fintech Data Analyst?

AspectFintech Data ScienceFintech Data Analyst
Required SkillsAdvanced statistical, programming, and machine learning skillsData interpretation, reporting, and basic analytics
CertificationsData Science certifications, programming coursesData analysis or business intelligence certifications
Work EnvironmentDeveloping models, algorithms, and predictive analyticsData reporting, dashboards, and data cleaning
Industry UsageCreating predictive models for risk, fraud detection, and customer insightsGenerating reports, supporting decision-making with data

Fintech Data Science involves building complex models and applying machine learning techniques, requiring advanced skills and certifications. Fintech Data Analysts focus on interpreting data, creating reports, and supporting business decisions with less technical complexity. Both roles are essential in the fintech industry but differ in technical depth and responsibilities.

Infographic showing various Fintech Data Science job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $119,312 per year, or $57.4 per hour.

Senior Data Scientist

Q2 India

Cary, NC • On-site

$140 - $200/hr

Other

Medical

Posted 3 days ago

New


Job description

Why Join Q2?

As passionate about our people as we are about our mission. Why Join Q2? 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.

What Makes Q2 Special?

Being as passionate about our people as we are about our mission. We celebrate our employees in many ways, including our “Circle of Awesomeness” award ceremony and day of employee celebration among others! We invest in the growth and development of our team members through ongoing learning opportunities, mentorship programs, internal mobility, and meaningful leadership relationships. We also know that nothing builds trust and collaboration like having fun. We hold an annual Dodgeball for Charity event at our Q2 Stadium in Austin, inviting other local companies to play, and community organizations we support to raise money and awareness together.

The Job At-A-Glance

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.

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 — including pricing recommendation, deal win likelihood, and anomaly detection — and see them through to production deployment
  • 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 both technical and non-technical audiences
Here’s What We’re Looking For
  • 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 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 with financial services, banking or fintech – commercial banking familiarity strongly preferred

This position requires fluent written and oral communication in English.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Benefits
  • Health & Wellness
  • Hybrid Work Opportunities
  • Flexible Time Off
  • Career Development & Mentoring Programs
  • Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents
  • Community Volunteering & Company Philanthropy Programs
  • Employee Peer Recognition Programs – “You Earned it”
Our Culture & Commitment

We’re proud to foster a supportive, inclusive environment where career growth, collaboration, and wellness are prioritized. And our benefits go beyond healthcare - offering resources for physical, mental, and professional well-being. Q2 employees are encouraged to give back through volunteer work and nonprofit support through our Spark Program (see more). We believe in making an impact—in the industry and in the community.

Equal Opportunity Employer

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status.

Applicants in California or Washington State may not be exempt from federal and state overtime requirements.

Mission

Q2’s mission is to build strong and diverse communities by strengthening their financial institutions. That mission shapes the technology we build, how we serve our customers, and how we show up for each other.

Vision

We started with a straightforward belief: technology could fundamentally change how financial institutions serve their communities. More than 20 years later, that belief still drives us.

Q2 delivers digital banking and lending solutions that help financial institutions deepen relationships, improve experiences, and grow. Across every department and region, Q2 team members bring creativity, collaboration, and purpose to building technology that makes banking stronger, easier, and more human.

Culture & Values

Q2’s culture is built by Q2ers and grounded in ten guiding principles that define how we show up for each other, our customers, and our communities. We take our mission seriously. We also have fun doing it. Teams across the company work together to solve hard problems, move quickly, and make a real impact on the financial institutions and communities we serve. We’re also helping shape how AI is applied in financial services, bringing the same disciplined, banking‑first approach Q2 has practiced for more than 20 years to this next chapter of innovation.

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