1

Data Science Associate Jobs in Texas (NOW HIRING)

Data Scientist Level 3

Boerne, TX · On-site

$92K - $126K/yr

... an Associate's degree required. * Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science * A ...

... an Associate's degree required. * Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science * A ...

About this role In Gartner's Services Data Science team, we innovate the way our team helps clients ... That's why we hire associates with the intellectual curiosity, energy and drive to want to make a ...

About this role In Gartner's Services Data Science team, we innovate the way our team helps clients ... That's why we hire associates with the intellectual curiosity, energy and drive to want to make a ...

next page

Showing results 1-20

Data Science Associate information

See Texas salary details

$53.6K

$63.4K

$120.2K

How much do data science associate jobs pay per year?

As of Jun 9, 2026, the average yearly pay for data science associate in Texas is $63,389.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,000.00 and $55,400.00 per year, depending on experience, location, and employer.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is data science dead in 10 years?

Data Science Associate roles are expected to remain relevant in the next decade as organizations continue to rely on data-driven decision making. Advances in automation and AI may change some tasks, but skills in statistical analysis, programming, and machine learning will still be valuable for interpreting complex data. Continuous learning and adapting to new tools like Python, R, and cloud platforms will be important for future success in the field.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What are the key skills and qualifications needed to thrive as a Data Science Associate, and why are they important?

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

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

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What are the most commonly searched types of Data Science jobs in Texas? The most popular types of Data Science jobs in Texas are:
What are popular job titles related to Data Science Associate jobs in Texas? For Data Science Associate jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Science Associate jobs in Texas look for? The top searched job categories for Data Science Associate jobs in Texas are:
What cities in Texas are hiring for Data Science Associate jobs? Cities in Texas with the most Data Science Associate job openings:
Principal Associate, Data Scientist - Frontier AI in Customer Protection

Principal Associate, Data Scientist - Frontier AI in Customer Protection

Capital One

Plano, TX

$56K - $56K/yr

Full-time

Posted 18 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

72nd of 141 rated banks


Job description

Principal Associate, Data Scientist - Frontier AI in Customer Protection

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

The Retail Bank Customer Protection Data Science team has a relentless focus on innovation with a passion for improving customer experiences around fraud prevention. This team is focused on detecting and thwarting fraud and scams that target our customers and threaten their financial well-being and feelings of safety. Detecting and preventing fraud behaviors as early as possible helps keep customer funds secure and enables the Bank to grow with confidence. Our team is constantly investing to improve and complement existing model-based defenses with the latest and greatest techniques from industry and academia. We use data to proxy the real world signals that help us find fraud and engineer our way to using this in production with SQL and Python-centric methods.

Role Description

In this role, you will:

  • Leverage a broad stack of technologies - Python, Conda, AWS, Spark, Gremlin, NeptuneDB, and more - to build knowledge graphs and graph algorithms that uncover hidden connections in structured and unstructured data

  • Pilot graph modeling algorithms through all phases of development, from design through training, evaluation, validation, and implementation

  • Connect your deep technical modeling expertise to the pressing business goals of our fraud prevention strategy partners to create exciting solutions to demanding challenges

  • Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading fraud defenses

The Ideal Candidate is:

  • Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.

  • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.

  • Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

  • A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:

    • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics

    • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics

    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Preferred Qualifications:

  • Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)

  • At least 3 years' experience with Knowledge Graphs or similar data

  • At least 1 year experience working with Graph database management (NeptuneDB, Neo4j, etc)

  • At least 1 year experience working with Graph query languages (Gremlin, Cypher, etc)

  • At least 1 year of experience working with AWS

  • At least 3 years' experience in Python, Scala, or R

  • At least 3 years' experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Plano, TX: $147,100 - $167,900 for Princ Associate, Data Science


New York, NY: $176,500 - $201,400 for Princ Associate, Data Science


McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science









Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


What Capital One employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom