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Fintech Data Science Jobs in Seattle, WA (NOW HIRING)

Strategic Finance Analyst II

Bellevue, WA · On-site

$110K - $143K/yr

... Data Science, Computer Science , or a related field. * 2-5 Years of Experience: Background in Finance, Investment Banking, Consulting, or Data Analytics. Experience in SaaS, Cloud, Data, or Fintech ...

Machine Learning Engineer

Bellevue, WA · On-site

$161.14 - $200/hr

FinTech is one of the most complex and rapidly evolving spaces in technology, and the challenges we ... Work closely with other engineering teams, data scientists, and the marketing team to integrate ...

Write scalable software that helps us efficiently handle the large volumes of data on our platform ... Computer Science Industry Keywords * Fintech * Payment Processing * Accounting Concepts Tools ...

Agentic Analytics Engineer

Seattle, WA · On-site

$186K - $256K/yr

This is a high-impact IC role at the intersection of data science, data engineering, and AI ... Experience in real estate, fintech, or marketplace businesses * Background in marketing analytics ...

Director, USDC Application Product

Seattle, WA · On-site +1

$265K - $277K/yr

Partner with Marketing and Data Science on attribution, referral/viral mechanics, and paid/organic ... Experience in fintech, payments, wallets, or consumer finance products * Familiarity with crypto ...

Lifecycle Marketing Lead

Seattle, WA · On-site

$162 - $195/hr

Partner with Data Science, User Acquisition, and Product Marketing on personalization and ... Fintech background is a plus but not required, especially if you come from a strong subscription ...

Showing results 21-40

Fintech Data Science information

See Seattle, WA salary details

$42.7K

$139.7K

$223.6K

How much do fintech data science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for fintech data science in Seattle, WA is $139,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $154,800.00 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.

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.

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 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.

Is data science good for fintech?

Data science is highly valuable in fintech, as it enables the development of algorithms for risk assessment, fraud detection, and personalized financial services. Fintech companies often rely on data analysis, machine learning, and statistical modeling to improve decision-making and customer experience. Skills in programming, data manipulation, and financial knowledge are essential for data scientists in this field.

Is fintech data science a high paying career?

Fintech data science is generally a high-paying career due to the demand for advanced analytics and machine learning skills in financial technology companies. Salaries often depend on experience, education, and technical expertise in tools like Python, R, and SQL, with senior roles earning significantly more. The field offers competitive compensation compared to many other data science roles across industries.
Infographic showing various Fintech Data Science job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $139,680 per year, or $67.2 per hour.

Senior Applied Scientist, FinTelligence

Amazon

Bellevue, WA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 3 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,107 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

At Amazon's FinTech organization, we are building AI systems that process hundreds of millions of financial transactions, turn complex documents into actionable intelligence, and power autonomous agents that learn from every customer interaction. We are looking for a Senior Applied Scientist to lead the development of generative AI applications that change how finance teams work, tackling problems at the intersection of large language models, multi-agent systems, and real-world financial operations.
Key job responsibilities
What You'll Work On
- Building AI systems that finance teams trust enough to rely on without manual review, where precision isn't a nice-to-have, it's a compliance requirement
- Designing agents that learn from user corrections and get measurably better with every interaction, not just at the next model release
- Solving inference at massive scale using tiered model architectures, intelligent routing, and small language models that deliver production-grade accuracy at a fraction of frontier model cost
- Developing evaluation frameworks that catch quality regressions before customers do and gate every model change before it ships
Who Thrives Here
- You're someone who cares as much about shipping as about research.
- You've built models that run in production, not just in notebooks.
- You're comfortable working across the full stack, from model architecture to deployment to measuring whether the customer's workflow actually changed.
- You operate well in cross-functional settings where science, engineering, and business teams inform each other continuously.
- You'd rather solve a hard real-world problem than optimize a benchmark.
What Makes This Different
Your work ships to production and directly changes how thousands of finance professionals operate daily
The problems are genuinely hard: financial data is messy, regulated, high-stakes, and operates at a scale where naive LLM approaches break down
You'll work across multiple domains - from contract intelligence to cash application to financial data investigation - not a single narrow use case
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 6+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- Experience with neural deep learning methods and machine learning
- Experience programming in Java, C++, Python or related language
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Have publications at top-tier peer-reviewed conferences or journals
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue - 167,100.00 - 226,100.00 USD annually

What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US