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Data Science Machine Learning Jobs in Texas (NOW HIRING)

Stay current with emerging trends in data science, machine learning, and AI, and contribute to the team's knowledge sharing and continuous improvement culture. Serious candidates will possess the ...

Stay current with emerging trends in data science, machine learning, and AI, and contribute to the team's knowledge sharing and continuous improvement culture. Serious candidates will possess the ...

Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

Posted today

Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

Posted today

Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

Posted today

Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

Posted today

Stay current with developments in machine learning, statistical modeling, AI techniques, and responsible AI practices. Required Qualifications * Bachelor s or master s degree in Data Science ...

You will partner closely with Product Management, Data Science, Machine Learning Engineering, Search Engineering, Customer Experience, and senior technology leaders to deliver strategic initiatives ...

You will partner closely with Product Management, Data Science, Machine Learning Engineering, Search Engineering, Customer Experience, and senior technology leaders to deliver strategic initiatives ...

You will partner closely with Product Management, Data Science, Machine Learning Engineering, Search Engineering, Customer Experience, and senior technology leaders to deliver strategic initiatives ...

You will partner closely with Product Management, Data Science, Machine Learning Engineering, Search Engineering, Customer Experience, and senior technology leaders to deliver strategic initiatives ...

Staff Data Scientist

Dallas, TX · On-site

$153.90 - $220/hr

You will leverage your deep expertise in data science, applied AI, and machine learning to solve complex challenges, enhance our product offerings, and deliver actionable insights that propel our ...

Automate data workflows, model deployment, and reporting processes using scripting, CI/CD tools, and cloud-based technologies. • Research and evaluate emerging data science, machine learning, and ...

Stay current with developments in machine learning, statistical modeling, AI techniques, and responsible AI practices. Required Qualifications * Bachelor's or master's degree in Data Science ...

Showing results 41-60

Data Science Machine Learning information

See Texas salary details

$34.9K

$114.3K

$183.1K

How much do data science machine learning jobs pay per year?

As of Aug 12, 2026, the average yearly pay for data science machine learning 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 are the key skills and qualifications needed to thrive as a data science machine learning professional?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What are some common challenges faced when deploying machine learning models as a data science machine learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.
Infographic showing various Data Science Machine Learning job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $114,350 per year, or $55 per hour.

Data Scientist II

Swbc

San Antonio, TX

Full-time

Medical, Retirement

Re-posted 15 days ago


SWBC rating

6.5

Company rating: 6.5 out of 10

Based on 17 frontline employees who took The Breakroom Quiz


Job description

SWBC is seeking a talented individual who will contribute to the development of machine learning models, analytical solutions, and AI-driven capabilities that directly impact business performance and client outcomes. This role works closely with the Senior Data Scientist, Analytics Engineers, and Data Analysts to design, build, and deploy data science solutions within SWBC's modern, cloud-native data ecosystem and enterprise AI/ML platform. The Data Scientist II is expected to independently lead analyses and model development projects with minimal guidance, while contributing to the broader AI strategy of the organization.

Why you'll love this role:

In this role, you will work hands-on with cutting-edge tools and platforms every day, including Hex for experimentation, Omni for AI context development powering Clara, and SWBC Intelligence our multi-model AI orchestration platform spanning AWS Bedrock and AWS Sagemaker to build and deploy intelligent solutions for internal and client-facing use cases. We offer a collaborative environment that values continuous learning, empirical rigor, and professional growth.

Essential duties include the following:

  • Design, develop, and deploy machine learning models and analytical solutions to address business problems, including forecasting, segmentation, classification, and anomaly detection.
  • Contribute to the development and enhancement of Clara, SWBC's AI decision assistant, including supporting context engineering within Omni, prompt development, and model evaluation workflows.
  • Build and maintain ML/AI experiment workflows using Hex for prototyping and exploration, and AWS SageMaker and MLflow for experiment tracking, feature engineering, and model versioning.
  • Develop and deploy AI/ML solutions within SWBC Intelligence, the enterprise multi-model AI orchestration platform, leveraging AWS Bedrock and AWS Sagemaker as directed by senior team members.
  • Conduct exploratory data analysis and feature engineering using data sourced from SWBC's governed medallion architecture (Bronze - Silver - Gold) in Snowflake.
  • Participate in the platform's Evaluation Harness process, including test case development, model benchmarking, and scoring framework contribution to ensure solution quality.
  • Perform AI experimentation and prototyping within governed sandbox environments, including Snowflake Sandbox and Hex, ensuring adherence to data privacy and compliance requirements.
  • Apply Responsible AI principles, including bias detection, model explainability, and fairness monitoring, to all model development activities.
  • Collaborate with cross-functional teams including Analytics Engineering, Data Management, and business stakeholders to translate business problems into data science solutions.
  • Communicate findings, model results, and recommendations to both technical and non-technical audiences through clear documentation, visualizations, and presentations.
  • Stay current with emerging trends in data science, machine learning, and AI, and contribute to the team's knowledge sharing and continuous improvement culture.

Serious candidates will possess the minimum qualifications:

  • Master's degree in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics, or a related discipline. Equivalent professional experience (5+ years) may be considered in lieu of an advanced degree.
  • Minimum of two (2) years of progressive experience in data science, analytics, or machine learning roles.
  • Proficiency in Python and SQL, with working knowledge of ML frameworks such as TensorFlow, PyTorch, scikit-learn, or equivalent.
  • Experience developing and deploying models within cloud-based AI/ML platforms, preferably AWS (SageMaker, S3) and Snowflake.
  • Familiarity with MLOps tools and practices, including MLflow, experiment tracking, and model versioning.
  • Proficiency in Hex for data science experimentation and prototyping.
  • Understanding of statistical modeling, hypothesis testing, and experimental design.
  • Ability to work with structured and semi-structured data, perform data cleaning, and conduct exploratory analysis.
  • Strong communication skills with the ability to present findings to both technical and non-technical audiences.
  • Ability to interpret ambiguity and work with minimal direction on defined project scopes.
  • Ability to lift 20 lbs. of files, supplies, documents, or other related items.

SWBC offers*:

  • Competitive overall compensation package
  • Work/Life balance
  • Employee engagement activities and recognition awards
  • Years of Service awards
  • Career enhancement and growth opportunities
  • Leadership Academy and Mentor Program
  • Continuing education and career certifications
  • Variety of healthcare coverage options
  • Traditional and Roth 401(k) retirement plans
  • Lucrative Wellness Program

*Based upon employee eligibility

Additional Information:

SWBC is a Substance-Free Workplace and requires pre-employment drug testing.

Please note, SWBC does not hire tobacco users as allowed by law.

To learn more about SWBC, visit our website at www.SWBC.com. If interested, please click the appropriate apply button.


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