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Data Science Analytics Jobs in Texas (NOW HIRING)

Fraud Data Analyst

Richardson, TX · On-site +1

$77K - $132K/yr

Partner with Risk Data Science & Analytics to translate dashboards, models, features, risk scores, and analytical insights into practical fraud decision strategies and operational controls.

Fraud Data Analyst

Richardson, TX · On-site

$77K - $132K/yr

Partner with Risk Data Science & Analytics to translate dashboards, models, features, risk scores, and analytical insights into practical fraud decision strategies and operational controls.

New

Data Science and Analytics team leadership. Manage data analysts delivering dashboards, recurring reports, and ad-hoc analysis. Establish consistent standards for data science and analytics ...

Sr. Data Scientist

Richardson, TX · On-site

$113K - $148K/yr

Bachelor's degree in computer science, Data Science, Analytics, Statistics, Business, Information Science, or a related field with 5+ years of experience in data science, analytics, machine learning ...

Showing results 41-60

Data Science Analytics information

See Texas salary details

$22

$51

$88

How much do data science analytics jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for data science analytics in Texas is $51.00, according to ZipRecruiter salary data. Most workers in this role earn between $40.96 and $57.79 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data science analytics professional?

To thrive in Data Science Analytics, a strong background in statistics, data modeling, and programming (often with a degree in computer science, mathematics, or a related field) is essential. Familiarity with tools such as Python, R, SQL, and data visualization platforms like Tableau or Power BI, as well as knowledge of machine learning libraries, is typically required. Critical thinking, problem-solving, and effective communication skills help professionals translate complex data insights into actionable business strategies. These competencies are crucial for extracting meaningful information from data and driving informed decision-making within organizations.

How do data science analytics professionals typically collaborate with other departments within an organization?

Data science analytics professionals often work closely with teams across the organization, such as marketing, finance, product development, and IT. Their role involves understanding business needs, gathering requirements, and translating complex data findings into actionable insights for non-technical stakeholders. Effective communication and teamwork are essential, as data scientists may participate in cross-functional meetings, present their analyses, and tailor their recommendations to support strategic decision-making. This collaborative approach not only enhances the impact of analytics projects but also fosters continuous learning and innovation within the organization.

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

AspectData Science AnalyticsData Analyst
Required CredentialsDegree in Data Science, Statistics, or related fields; programming skillsDegree in Statistics, Mathematics, or related fields; proficiency in Excel and SQL
Work EnvironmentOften involves complex modeling, machine learning, and predictive analyticsFocuses on data cleaning, reporting, and visualization
Employer & Industry UsageTech companies, finance, healthcare, and research institutionsBusiness, marketing, finance, and operations across various industries

Data Science Analytics and Data Analysts both work with data, but Data Science Analytics typically involves advanced modeling and predictive techniques, while Data Analysts focus on data reporting and visualization. The roles often overlap, but Data Science Analytics requires more technical skills and a deeper understanding of algorithms.

What is data science analytics?

Data science analytics is the process of extracting insights and knowledge from data using statistical, mathematical, and computational techniques. It involves collecting, cleaning, analyzing, and visualizing data to help organizations make informed decisions. Professionals in this field use tools like Python, R, and SQL to interpret complex data sets, build predictive models, and identify trends or patterns. Data science analytics plays a key role in industries such as finance, healthcare, retail, and technology, enabling businesses to optimize operations and improve outcomes.

What are the most commonly searched types of Data Science Analytics jobs in Texas?

The most popular types of Data Science Analytics jobs in Texas are:

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

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

Infographic showing various Data Science Analytics 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 $106,090 per year, or $51 per hour.

Senior Data Science Manager - Strategic Data Solutions

Apple

Austin, TX • On-site

Full-time

Posted 25 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th 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.
Apple's Strategic Data Solutions team is looking for an accomplished data science and analytics leader to build and lead a diverse team of senior individual contributors who are experts in analytics and experimentation. You'll primarily partner with machine learning engineering leaders to deliver high-impact science and analytics that power decision automation and optimize performance across a wide range of business goals.
Description
• Hire, grow, and lead a high-caliber team of data professionals spanning analytics engineering and experimentation
• Guide team members in delivering data/business analytics, data storytelling, architecture guidance, and performance optimization
• Ensure data integrity, accessibility, and consistency across systems by overseeing data transformation and integration from multiple sources
• Design and implement robust monitoring, alerting, and health check programs to ensure sustained data and model performance at scale
• Drive experimentation and statistical analysis to uncover actionable insights and inform decision-making across business domains
Partner with cross-functional leaders to align analytics initiatives with strategic objectives
• Evangelize data science best practices and help embed a data-informed culture across teams
• Lead through influence - balancing technical mentorship with strategic thinking to enable scalable, high-impact outcomes
Minimum Qualifications
Bachelor's degree in Computer Science, Statistics, Applied Math, Engineering, or a related field
7+ years of hands-on experience in data science, analytics engineering, or similar technical analytics roles
2+ years of experience leading and mentoring data-focused teams
Proficiency in SQL and at least one programming language (e.g., Python, R)
Strong background in experimentation design, causal inference, and statistical analysis
Experience working with large-scale data pipelines and production-level analytics systems
Proven ability to drive measurable business impact through data and automation
Preferred Qualifications
Experience with building robust monitoring systems to track data and model health in production
Expertise in data storytelling and creating stakeholder-ready visualizations and narratives
Ability to connect insights to business outcomes and influence strategy
Familiarity with modern data platforms (e.g., Spark, Snowflake, Airflow) and ML Ops tooling
Passion for fostering inclusive team environments and valuing diverse perspectives
Clear communicator who can translate complex technical concepts into actionable business language

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