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Fintech Data Science Jobs (NOW HIRING)

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

Data Scientist

New York, NY · On-site

$190K - $262K/yr

... Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences. We are a product analytics team embedded in key product areas ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

We're Fiserv, a global leader in Fintech and payments, and we move money and information in a way ... Translate business objectives into data science solutions that improve customer acquisition ...

Credit Strategy Data Scientist

CA · Remote

$50 - $53.33/hr

Minimum 2 years of experience in risk analytics, data analysis, or data science within the Fintech or online payments industry. * Bachelors degree in computer science, Engineering, Mathematics ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

... Science, Data Engineering, Statistics, or related field.) * 0 - 1 years of experience (preferably in Data or BI) About Fintech: For over 35 years, Fintech LLC has redefined how over 1.1 million B2B ...

Flex is a growth-stage, NYC headquartered FinTech company that is creating the best rent payment ... data science/analyst work * Strong SQL and hands-on experience with dbt and Snowflake (or ...

As a Senior Pre-Sales Solution Consultant, Fintech , you will be the primary technical point-of ... You will collaborate closely with Sales, Data Science, Product, Engineering, and Customer Success ...

The Director, Data Science - Competitive Intelligence, AI Insights & Strategic Analytics is a ... Experience within Financial Services, Consumer Lending, Credit Cards, Banking, Payments, or FinTech ...

Showing results 41-60

Fintech Data Science information

See salary details

$37.5K

$122.7K

$196.5K

How much do fintech data science jobs pay per year?

As of Sep 1, 2026, the average yearly pay for fintech data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 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.
More about Fintech Data Science jobs

What cities are hiring for Fintech Data Science jobs?

Cities with the most Fintech Data Science job openings:

What states have the most Fintech Data Science jobs?

States with the most job openings for Fintech Data Science jobs include:

Infographic showing various Fintech Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist

Atlanta, GA • On-site


FIS
IT Services • 10K+ employees

7.4

Company rating: 7.4 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

170th of 247 rated software companies

Good employer

Paid breaks


Full-time

Posted 6 days ago


Job description

Job Description

Are you curious, motivated, and forward-thinking? At FIS you'll have the opportunity to work on some of the most challenging and relevant issues in financial services and technology. Our talented people empower us, and we believe in being part of a team that is open, collaborative, entrepreneurial, passionate and above all fun.

About the role:

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory analysis as well as predictive models and AI solutions to solve business problems across the financial services industry, particularly in Risk, Fraud, Marketing, and Portfolio Management. Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally.

What you'll be doing:

  • Participate in the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.
  • Leverage expertise in data structures and algorithms to analyze and prepare data for modeling, assembling datasets from both standard and novel data sources and incorporate them into end-to-end analytical solutions.
  • Apply advanced machine learning, predictive analytics, natural language processing (NLP), and emerging AI techniques (GenAI, Agentic etc.) to solve complex business problems across the payments and financial services ecosystem.
  • Design and execute experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.
  • Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization.
  • Stay current on industry trends in machine learning, AI, Generative AI, and financial services analytics; bring relevant innovations to the team.

What you bring:

  • Master's degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative discipline.
  • 1-3 years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions within the Payments, Banking, or Financial Services industry.
  • Strong proficiency in Python and SQL; experience with big data technologies such as Spark, PySpark, a plus.
  • Hands-on experience with data wrangling, feature engineering, and model development using libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, or Plotly.
  • Demonstrated experience building and deploying machine learning models in a production or near-production environment.
  • Proficiency with data visualization and business intelligence tools (e.g., Tableau or equivalent).
  • Strong analytical thinking and problem-solving skills; ability to translate ambiguous business problems into rigorous analytical frameworks.
  • Ability to work collaboratively across product, engineering, and business teams.

Nice to have:

  • Experience within the Payments, Banking, or Financial Services industry.
  • Hands-on experience with the Databricks platform, including MLflow, Model Registry, collaborative notebooks, and MLOps workflows.
  • Experience deploying cloud-native machine learning solutions, particularly within AWS environments.
  • Familiarity with emerging advancements in Transformer Models and Agentic AI technologies.
  • Knowledge of model governance, regulatory compliance, and MLOps best practices within regulated financial services environments.

What we offer you:

A career at FIS is more than just a job. It's the chance to shape the future of fintech. At FIS, we offer you:

  • A voice in the future of fintech
  • Always-on learning and development
  • Collaborative work environment
  • Opportunities to give back
  • Competitive salary and benefits


Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

EEOC Statement

FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here


For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.

Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.

#pridepass


FIS logo

About FIS

Sourced by ZipRecruiter

FIS is a leader in technology and services that helps businesses and communities thrive by advancing commerce and the financial world. For over 50 years, FIS has continued to drive growth for clients around the world by creating tomorrow’s technology, solutions and services to modernize today’s businesses and customer experiences. By connecting merchants, banks and capital markets, we use our scale, apply our deep expertise and data-driven insights, innovate with purpose to solve for our clients’ future, and deliver experiences that are more simple, seamless and secure to advance the way the world pays, banks and invests. Headquartered in Jacksonville, Florida, FIS employs more than 55,000 people across 50+ countries, dedicated to helping our clients be ahead of what’s next. FIS offers more than 450 solutions and processes over $75b of transactions around the planet. FIS is a Fortune 500® company and is a member of Standard & Poor’s 500® Index.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Jacksonville , FL, US

Year founded

1968

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What FIS Global employees say

Pay

Benefits

Hours and flexibility

Workplace

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