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Data Science Analytics Jobs in Texas (NOW HIRING)

Lennox International

Data Scientist II

Richardson, TX · On-site

$88K - $115K/yr

Bachelor's degree in computer science, Data Science, Analytics, Statistics, Business, Information Science, or a related field with 3+ years of experience in data science, analytics, machine learning ...

Ci

Data Science and Analytics Manager

Austin, TX

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 ...

Lennox International

Data Scientist II

Richardson, TX · On-site

$88K - $115K/yr

Bachelor's degree in computer science, Data Science, Analytics, Statistics, Business, Information Science, or a related field with 3+ years of experience in data science, analytics, machine learning ...

Syntricate Technologies

Data Science

Austin, TX · On-site

Syntricate Technologies is seeking a Data Science professional to join their team. The role ... Syntricate Technologies offers quality assurance, validation, regulatory, business analysis, and ...

Analytica

Data Scientist

San Antonio, TX · On-site

$110 - $150/hr

This role will independently develop and deliver data science and AI solution components while owning assigned analytics, data processing, model development, visualization, and decision-support work ...

Mars Technominds Inc

Data Science Architect

Mckinney, TX · On-site

$59 - $76/hr

Lead the architecture and implementation of predictive analytics, machine learning, statistical modeling, and advanced analytics solutions. * Collaborate with Data Scientists and Data Engineers to ...

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Data Science Analytics information

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$22

$51

$88

How much do data science analytics jobs pay per hour?

As of Sep 6, 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 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 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 can I do with data science analytics?

Data science analytics involves analyzing large datasets to extract insights, support decision-making, and solve complex problems. Professionals in this field use tools like Python, R, and SQL, and often work in industries such as finance, healthcare, or marketing to develop predictive models and visualize data. Skills in statistics, machine learning, and data visualization are essential for success in this role.

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:

What job categories do people searching Data Science Analytics jobs in Texas look for?

The top searched job categories for Data Science Analytics jobs in Texas are:

Data Science Analytics jobs near you
Infographic showing various Data Science Analytics job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $106,090 per year, or $51 per hour.

Senior Backend Software Engineer, Platform Engineering, Services Data Science & Analytics

Apple

Austin, TX • On-site

$121K - $160K/yr

Full-time

Re-posted 10 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 683 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Are you ready to make a significant impact on how one of the world's largest analytics organizations moves, serves, and governs its data? If you are passionate about building high-performance, reliable platform services at internet scale, we would love for you to apply! The Apple Services Data Science & Analytics organization drives decisions that improve the customer experience, accelerate growth, and uncover new business opportunities while respecting user privacy and adhering to regulatory policy. We work on some of the largest e-commerce and media streaming businesses in the world and have an incredible team collaborating on the best ways to improve these services for our customers! Our culture is built on rapid iteration, open debate, and independent thinking - we take calculated risks and work as analytical advisors across product, design, engineering, marketing, editorial, legal, and business teams.
Description
As a Senior Software Engineer on the Services Data Science & Analytics Platform Engineering team, you will design, build, and operate the backend services that form the foundation of DS&A's data platform.
This is high-stakes infrastructure work: every downstream consumer in DS&A and Services broadly depends on what you build. A great fit for this role is someone who thinks deeply about distributed systems, obsesses over reliability and performance, and takes pride in building platform primitives that other engineers love to build on.
Minimum Qualifications
8+ years of experience building and operating high-performance, production-grade backend API services
Expert proficiency in Python or Node.js/TypeScript - including async programming, type safety, and framework-level development (FastAPI, Express, or equivalent)
Demonstrated experience designing and operating distributed systems with strict reliability and latency SLAs
Strong proficiency with API design and service-to-service communication patterns (REST, gRPC, GraphQL, or equivalent)
Hands-on experience with multi-layer caching architectures (in-process, Redis, or similar) and cache invalidation strategies
Extensive experience building systems that integrate with distributed and high-performance data stores - Snowflake, Trino, Spark, PostgreSQL, or equivalent
Proficiency with Kubernetes, deployment, HPA, StatefulSets, namespace management
Strong observability practice, Prometheus, Grafana, OpenTelemetry, or equivalent
BS in Computer Science, Engineering, or related field, or equivalent professional experience
Preferred Qualifications
Experience building data catalog, metadata, or lineage systems
Familiarity with Apache Iceberg or other open table formats
Experience with CI/CD pipeline design and enforcement gates in large engineering organizations
Familiarity with AI/ML infrastructure or experience integrating LLM-powered capabilities into platform services
MS in Computer Science, Engineering, or related field

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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