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Fintech Data Science Jobs in Texas (NOW HIRING)

One Park Financial

Senior Data Scientist

Plano, TX · On-site

... fintech. * Professional Growth : We invest in our employees' growth with continuous learning ... Requirements * 4-7 years of experience in Data Science and the Financial Industry, preferably in ...

One Park Financial

Senior Data Scientist

Plano, TX · On-site

... fintech. * Professional Growth : We invest in our employees' growth with continuous learning ... Requirements * 4-7 years of experience in Data Science and the Financial Industry, preferably in ...

One Park Financial

Senior Data Scientist

Plano, TX

... fintech. * Professional Growth : We invest in our employees' growth with continuous learning ... Requirements * 4-7 years of experience in Data Science and the Financial Industry, preferably in ...

Thatch

Data Scientist, Analytics

Austin, TX · On-site +1

$160K - $200K/yr

We're looking for a Data Scientist to help Thatch make better product, commercial, financial, and ... Working in healthcare, fintech, or other complex, regulated domain. How we work * We move quickly ...

Fliff

Senior Data Scientist

Austin, TX · On-site

The Role: We're hiring a Senior Data Scientist to embed within the marketing and growth function ... Experience modeling promo and bonus economics in a gaming, fintech, or e-commerce context Benefits:

Fliff

Senior Data Scientist

Austin, TX · On-site +1

The Role: We're hiring a Senior Data Scientist to embed within the marketing and growth function ... Experience modeling promo and bonus economics in a gaming, fintech, or e-commerce context Benefits:

SentiLink Corp

Research Scientist, PhD New Grad

Austin, TX · On-site

$120 - $220/hr

... Forbes Fintech 50. We have also been named a 2026 FICO Industry Vanguard Decision Award Winner ... This is a full‑stack data science role, involving model development, analysis, and writing ...

Apex Fintech Solutions

Solutions Engineer

Austin, TX · On-site

WHO WE ARE Apex Fintech Solutions (Apex) powers innovation and the future of digital wealth ... Real-Time Data Processing: Familiarity with Apache Kafka, AWS Kinesis, or Google Pub/Sub is ...

CertifID LLC

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Partner with data science, engineering, Revenue Operations, and executive stakeholders to define ... Experience in fintech, cybersecurity, or fraud prevention . * Familiarity with data privacy ...

Apex Fintech Solutions

Sr Database Administrator

Austin, TX · On-site

$49.25 - $68/hr

WHO WE ARE Apex Fintech Solutions (Apex) powers innovation and the future of digital wealth ... Bachelor's degree in Computer Science, Computer Engineering (or equivalent work experience ...

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Showing results 21-40

All JobsFintech Data Science JobsFintech Data Science Jobs in Texas

Fintech Data Science information

See Texas salary details

$34.9K

$114.3K

$183.1K

How much do fintech data science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for fintech data science in Texas is $114,350.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,800.00 and $126,700.00 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.

What are popular job titles related to Fintech Data Science jobs in Texas?

For Fintech Data Science jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Fintech Data Science jobs in Texas look for?

The top searched job categories for Fintech Data Science jobs in Texas are:

What cities in Texas are hiring for Fintech Data Science jobs?

Cities in Texas with the most Fintech Data Science job openings:

Fintech Data Science jobs near you
Infographic showing various Fintech Data Science job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $114,350 per year, or $55 per hour.

Senior Data Scientist

One Park Financial

Plano, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago

Job description

Company Overview:
One Park Financial (OPF) is a leading Financial Technology company dedicated to empowering small businesses by connecting them with a wide variety of flexible financing and funding options. Our mission is to provide entrepreneurs with the working capital they need to elevate their businesses to new heights. At OPF, we believe in working with high-performing individuals who are ready to play an integral part in our company's expansion. We know that our success hinges on our people, and we strive to enable them to do what they do best.
Why Join Us?
At OPF, we foster a dynamic and inclusive company culture that emphasizes collaboration, innovation, and personal growth. Our team is composed of passionate, driven individuals who are committed to making a difference. Here's what you can expect when you join our team:
  • Innovative Environment: Work with cutting-edge technology and be part of a team that is constantly pushing the boundaries of fintech.
  • Professional Growth: We invest in our employees' growth with continuous learning opportunities, training programs, and career advancement paths.
  • Supportive Culture: Enjoy a supportive and inclusive work environment where your ideas are valued, and your contributions make a real impact.
  • Community Focus: Be part of a company that understands the importance of small and mid-sized businesses to their communities and the nation's financial health.
  • High-Performing Team: Join a team of badasses who are committed to excellence and are integral to our company's expansion and success.

About the Role
We are looking for a seasoned Senior Data Scientist to join our Analytics team to enable core business transformation. This role is about building and pressure-testing the models and proposals that drive how we price, approve, and grow, and doing it with the statistical and analytical rigor to prove they work before they ship.
You will own a production system end to end, helping operate and evolve our proprietary risk-based pricing engine, the application that powers our real-time offer decisioning.
You will work closely with business stakeholders to understand problems and propose & implement AI/ML solutions, and you will partner with DevOps, Product, and Engineering to take models from notebook to production.
You will lead the charge in A/B testing within the organization and design experiments to prove success. You will perform EDA, identify modeling opportunities, feature engineer & ETL data, implement models and their monitoring, and highlight opportunities for change.
We are an AI-forward company, and we expect our data scientists to work that way. We want someone who leans on modern AI and LLM tooling to make their own analysis, modeling, and experimentation faster and sharper, not someone who does things the slow, manual way.
We want to work with high-performing badasses who will play an integral part in our transformation of the company. We understand one thing: it all comes down to working with creative & committed people and enabling them to do what they do best.
Responsibilities
  • Utilize advanced statistical and machine learning techniques to analyze large datasets and build new AI/ML models.
  • Develop and pressure-test pricing and credit proposals end to end, with the statistical and analytical rigor to prove they will work before they ship. These won't always be models; sometimes the answer is a well-tested policy change.
  • Conduct exploratory data analysis, feature engineering, and data preprocessing to solve business problems.
  • Own, operate, and enhance our proprietary risk-based pricing engine (a production Python application), including its models, business logic, deployment, and monitoring.
  • Facilitate the deployment and monitoring of models for real-time and batch processing.
  • Own strong model governance: clear documentation and versioning, ongoing monitoring for drift and degradation, regular validation, and a defensible audit trail across the model lifecycle.
  • Partner with DevOps, Product, and Engineering teams to ship models and features to production, owning the rollout from staging to production, including CI/CD, monitoring, and rollback.
  • Perform model evaluation and validation on a regular basis to ensure robust performance.
  • Engineer A/B tests with scientific rigor. Gather test data and validate results to present to business stakeholders.
  • Use modern AI and LLM tooling to speed up your own work, from EDA and feature engineering to model prototyping, documentation, and testing.
  • Champion creative uses of existing data to solve business problems with intellectual curiosity.
  • Produce statistical and data analysis visuals (charts, infographics) to communicate findings clearly and effectively to a non-technical audience.
  • Collaborate with team members, product managers, and business stakeholders to identify opportunities for new and innovative AI/ML solutions.
  • Analysis areas could include Onboarding Credit, Ongoing Credit, Marketing segmentation, Voice-based analysis, Text mining, Sentiment analysis, Risk quantification, and Risk-based pricing.

Requirements
  • 4-7 years of experience in Data Science and the Financial Industry, preferably in Credit or Lending.
  • Master's degree in mathematics, statistics, computer science, or data science.
  • Experience in transforming existing processes with AI/ML-based approaches.
  • Proficiency in data manipulation. Excellent SQL and Python skills for data wrangling and ETL.
  • Hands-on AWS / cloud experience deploying and operating production ML services (compute, storage, IAM, containerized deployment).
  • Experience building or maintaining production applications and services, not just models in notebooks. You should be comfortable owning software in production.
  • Experience with dashboard tools such as PowerBI or other visualization tools.
  • Experience building credit or risk models for Financial Services, Lending, or Insurance.
  • Experience in validating models to identify ongoing improvements.
  • Rock Solid data science skillset: Exploratory Data Analysis, Feature Engineering, Fitting, Tuning, and Comparing models, and managing the model Lifecycle.
  • Experience with statistical modeling and data analysis using programming languages such as Python.
  • Experience in ML engineering, cloud-based deployment, and machine learning model lifecycle management.
  • Knowledge of best practices for financial and lending models (model risk management, model governance, and fair-lending considerations) is a big plus.
  • Comfort using modern AI and LLM tools to make your own analysis and modeling more efficient (a plus).
  • Experience with dbt (major plus).

Benefits
  • Competitive salary
  • Local & National Health Insurance
  • Dental and Vision insurance
  • Group Medical Bridge
  • 401k with Match
  • ID Protection: 100% covered by the company
  • Life Insurance: 100% covered by the company
  • Generous PTO and holidays
  • Growth and development opportunities
  • Dynamic and collaborative work environment
  • Company events and team-building activities

Apply