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Data Science Analytics Jobs in Texas (NOW HIRING)

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 ...

... data science, analytics, or related disciplines. • Minimum of 5 years of experience with software development lifecycle and methodologies. • Proficiency in programming languages such as Python, R ...

This role sits at the intersection of data science, data engineering, analytics engineering, and AI productization. The right person will pair strong technical depth with practical business judgment ...

This role sits at the intersection of data science, data engineering, analytics engineering, and AI productization. The right person will pair strong technical depth with practical business judgment ...

They are seeking a Staff Data Science Engineer to lead the design and delivery of scalable data science, machine learning, and analytics solutions that create measurable business value across the ...

Data Science Tutor

Edinburg, TX · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Data Science Tutor

Bryan, TX · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Solve complex analytical challenges across Valero's business units by developing advanced AI and data science solutions that deliver actionable insights into operational and commercial questions.

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Data Science Analytics information

See Texas salary details

$22

$51

$88

How much do data science analytics jobs pay per hour?

As of Jul 5, 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, and why are they important?

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 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:
Infographic showing various Data Science Analytics job openings in Texas as of June 2026, with employment types broken down into 1% As Needed, 49% Full Time, 39% Part Time, 1% Temporary, 9% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% 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

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

Apple

Austin, TX

$121K - $160K/yr

Full-time

Posted 7 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 666 frontline employees who took The Breakroom Quiz

5th 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.
","responsibilities":"You will own core platform services end-to-end - from API design and query routing through caching infrastructure and data lineage - ensuring they perform reliably at the scale and latency demands of one of the world's largest analytics organizations.
You'll collaborate closely with Data Engineering, Data Science, Machine Learning Engineering, Insight Engineering, and Core Engineering teams, making architectural decisions that directly shape the scalability and durability of DS&A's analytical foundation.
Over time, you'll influence platform strategy, mentor engineers across the team, and help drive the technical roadmap for how DS&A manages, governs, and serves its data at scale.
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
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

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