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Data Science Machine Learning Jobs in Texas (NOW HIRING)

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models for real production use cases * Perform feature engineering and data preparation for ...

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models for real production use cases * Perform feature engineering and data preparation for modeling ...

RealPage, Inc.

Data Scientist

Richardson, TX · On-site

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models for real production use cases * Perform feature engineering and data preparation for ...

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models for real production use cases * Perform feature engineering and data preparation for ...

Striveworks

Senior Machine Learning Engineer

Austin, TX · On-site +1

$121K - $160K/yr

Founded by data scientists and engineers, Striveworks set out to make the journey from deployment ... The Role As a Senior Machine Learning Engineer at Striveworks, you'll be challenged-and trusted-on ...

Select Minds LLC

Data Scientist

Dallas, TX · On-site

$65 - $75/hr

Roles & Responsibilities 6+ years of experience in Machine Learning and Data Science. • Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic Workflow, Statistical methods ...

Conga

Staff Data Scientist (AI/ML)

Boston, TX

Experience. 10+ years of professional experience in data science, machine learning, or AI, including 5+ years working on AI/ML or GenAI solutions. Proven track record of developing, deploying, and ...

SWBC

Data Scientist II

San Antonio, TX · On-site

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 ...

SWBC

Data Scientist II

San Antonio, TX · On-site

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 ...

Swbc

Data Scientist II

San Antonio, TX

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 ...

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Showing results 1-20

All JobsData Science Machine Learning JobsData Science Machine Learning Jobs in Texas

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 Jun 29, 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.

Which has more salary, CS or AI?

Data Science and Machine Learning roles in AI generally have higher salaries than traditional computer science positions due to specialized skills in deep learning, neural networks, and advanced algorithms. AI roles often require expertise in programming languages like Python and frameworks such as TensorFlow, which are highly valued in the job market. Salaries vary by experience, location, and industry, but AI-focused positions tend to offer higher compensation on average.

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

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 engineers make $500,000?

Senior data science and machine learning engineers with extensive experience, advanced skills in programming, statistical analysis, and deep learning, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at executive or specialized levels.

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.

Do data scientists work with machine learning?

Data scientists often work with machine learning as a core part of their role, developing models to analyze data and make predictions. They use tools like Python, R, and libraries such as scikit-learn or TensorFlow to build and deploy machine learning algorithms. Knowledge of statistics, programming, and data manipulation is essential for this work.

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.

Which 3 jobs will survive AI?

Data science and machine learning roles are expected to persist as they require complex problem-solving, domain expertise, and creativity that AI tools currently cannot fully replicate. Jobs involving strategic decision-making, ethical considerations, and interpersonal skills, such as data analysts, AI ethics specialists, and AI system trainers, are also likely to remain in demand. Continuous learning and proficiency with AI tools will be essential for these roles to adapt and thrive.
Data Science Machine Learning jobs near you
Infographic showing various Data Science Machine Learning job openings in Texas as of June 2026, with employment types broken down into 60% Full Time, 36% Part Time, 2% Contract, and 2% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $114,350 per year, or $55 per hour.
Data Scientist - Strategic Data Solutions

Data Scientist - Strategic Data Solutions

Apple

Austin, TX

Full-time

Posted 3 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 666 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Imagine what you could do here! The people here at Apple don’t just create products - they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts.
At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work. Here on the Apple Store Online team, we are responsible for Apple’s largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things.
As a Data Scientist, you will provide data driven insights to fight fraud. You will develop models, evaluate product launches, develop automated solutions to deliver timely alerts, find opportunities for future development by applying the bleeding edge scientific methods. You will partner with engineers, product, program and business leaders alongside other teams to bring better experiences to drive meaningful customer impact.
Description
Research and develop evaluation methods to address fraud. Solve difficult, non-routine analysis problems by applying statistical, machine learning and advanced analytical methods as needed.
- Design and execute observational and experimental studies of causal inference
- Work with large, complex data sets.
- Develop automated solutions to deliver insights and alerts
- Drive feature evaluation and product roadmap with insights","responsibilities":"Develop scalable data solutions to be used to drive analyses, reports, and insights
Influence upstream data model design, drive KPI definitions and develop customized data solutions
Measure impact of features and initiatives and help improve customer experience
Collaborate and influence cross functional partners to help deliver product objectives on time
Communicate results, insights and expectations to partners and senior leaders, bridge any gaps between technical and non-technical audiences. Be adept at messaging domain and technical content at a level appropriate for the audience.
Work independently in sophisticated and highly visible projects, identify risks and develop frameworks, regularly connect with collaborators and leadership teams.
Preferred Qualifications
PhD in Statistics, Mathematics, Data Science, Machine Learning, Physics, Engineering, Computer Science or equivalent
Experience applying LLMs to solve technical problems such as data analysis, data automation, synthetic data generation with proven ability to optimize model performance for accuracy and efficiency
Excellent product intuition, keen eye for design and customer pain point awareness
Experience developing anomaly detection and causal inference models
Minimum Qualifications
Masters in Statistics, Mathematics, Data Science, Machine Learning, Physics, Engineering, Computer Science or equivalent
Proficiency in data querying using SQL, Spark, or equivalent technologies
Proficiency in scripting languages for data processing and analysis (ex: Python, R, or Scala)
Excellent communication and multi-functional collaboration skills, ability to convey complex concepts to diverse audiences
At least 3 years experience working as a Data Scientist

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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