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Artificial Intelligence Data Scientist Jobs in Spring, TX

... artificial intelligence, signal processing, machine learning, optimization etc. in business ... D. in Mathematics, Statistics, Computer Science, Operations Research, Engineering Science. Top 3 ...

The Data Scientist will be responsible for fusing structured and unstructured data sources (e.g., FinCEN, open-source intelligence, geospatial data platforms such as ArcGIS) and developing automated ...

Lead AI and Data Science Engineer II

Houston, TX · On-site

$97K - $128K/yr

Lead AI and Data Science Engineer II Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent ...

Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering - At least one of the following: Certifications aligned to data engineering, machine ...

Showing results 21-40

Artificial Intelligence Data Scientist information

See Spring, TX salary details

$34.3K

$112.4K

$179.9K

How much do artificial intelligence data scientist jobs pay per year?

As of Aug 11, 2026, the average yearly pay for artificial intelligence data scientist in Spring, TX is $112,380.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,200.00 and $124,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an artificial intelligence data scientist?

To thrive as an Artificial Intelligence Data Scientist, you need strong expertise in statistics, machine learning, data analysis, and programming, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, and cloud platforms, along with certifications like TensorFlow Developer or Microsoft Certified: Azure AI Engineer Associate, is highly valuable. Critical thinking, problem-solving, and strong communication skills help you translate complex data findings into actionable business strategies and work effectively with cross-functional teams. These competencies ensure accurate model development, impactful AI solutions, and effective collaboration in a rapidly evolving technology landscape.

What is the difference between Artificial Intelligence Data Scientist vs Machine Learning Engineer?

AspectArtificial Intelligence Data ScientistMachine Learning Engineer
CredentialsDegree in Data Science, AI, or related fields; certifications in data analysis and AI toolsDegree in Computer Science, Software Engineering, or related fields; certifications in ML frameworks
Work EnvironmentResearch-focused, data analysis, model development, often in collaborative teamsSoftware development, deploying ML models into production, often in engineering teams
Industry UsageTech, finance, healthcare, research institutionsTech companies, startups, industries requiring scalable ML solutions
Common Search IntentUnderstanding AI data analysis roles, data modeling, research tasksImplementing and deploying ML models, software engineering tasks

While both roles involve machine learning and AI, Artificial Intelligence Data Scientists focus on analyzing data, developing models, and research, whereas Machine Learning Engineers primarily build, deploy, and maintain scalable ML systems in production environments.

How do artificial intelligence data scientists typically collaborate with software engineers and domain experts on projects?

Artificial Intelligence Data Scientists often work closely with software engineers to integrate machine learning models into production systems, ensuring that data pipelines and algorithms are robust and scalable. They also collaborate with domain experts to better understand the business context, define problem statements, and interpret model results. This cross-functional teamwork is crucial for developing effective AI solutions that address real-world challenges and deliver value to the organization.

What is an artificial intelligence data scientist?

An Artificial Intelligence Data Scientist is a professional who uses advanced analytics, machine learning, and statistical methods to interpret complex data, build predictive models, and develop AI-driven solutions. They work with large datasets to extract valuable insights and help organizations make data-driven decisions. Their responsibilities often include data preprocessing, feature engineering, algorithm selection, model training and evaluation, and communicating results to stakeholders. AI Data Scientists typically have strong programming skills (such as Python or R), knowledge of statistics, and experience with machine learning frameworks.
What are popular job titles related to Artificial Intelligence Data Scientist jobs in Spring, TX? For Artificial Intelligence Data Scientist jobs in Spring, TX, the most frequently searched job titles are:
What cities near Spring, TX are hiring for Artificial Intelligence Data Scientist jobs? Cities near Spring, TX with the most Artificial Intelligence Data Scientist job openings:
Infographic showing various Artificial Intelligence Data Scientist job openings in Spring, TX as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $113,016 per year, or $54.3 per hour.

Manager, Data Science - PULSE Network, Business Intelligence

Capital One

Houston, TX • Hybrid

Full-time

Re-posted 27 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

93rd of 171 rated banks


Job description

Manager, Data Science - PULSE Network, Business Intelligence

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 Manager, Data Science 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:

As a Data Scientist in the PULSE Business Intelligence team, you will work closely with Pricing, Analytics and Relationship management, product and finance teams to deliver data-driven insights that support strategic business decisions. We focus on transforming complex large data into actionable intelligence that helps optimize pricing strategies, protect and grow revenue, strengthen relationships with partners and improve overall business performance. We are seeking a Data Scientist to support pricing strategy through advanced analytics, predictive modeling.

In this role, you will:

  • Partner with a cross-functional team of pricing analysts, finance analysts, data analysts and data engineers to optimize revenue.

  • Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data

  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The Ideal Candidate is:

  • 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.

  • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.

  • Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.

  • 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 6 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 4 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) plus 1 year of experience performing data analytics

  • At least 1 year of experience leveraging open source programming languages for large scale data analysis

  • At least 1 year of experience working with machine learning

  • At least 1 year of experience utilizing relational databases

Preferred Qualifications:

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

  • At least 1 year of experience working with AWS

  • At least 4 years' experience in Python, Scala, or R for large scale data analysis

  • At least 4 years' experience with machine learning and statistical modeling techniques.

  • At least 4 years' experience with SQL

  • Experience with large-scale transaction datasets.

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

This role is Hybrid, with associates expected to consistently spend three days per week in the office.

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: $179,400 - $204,700 for Mgr, Data Science


McLean, VA: $197,300 - $225,100 for Mgr, Data Science


Richmond, VA: $179,400 - $204,700 for Mgr, Data Science


Houston, TX: $179,400 - $204,700 for Mgr, 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).


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