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Data Science Developer Jobs in Texas (NOW HIRING)

Cypress HCM

Data Science Engineer

Austin, TX · Hybrid

$65 - $69.72/hr

Data Science Engineer Job Details * Data Science Engineer (Contract) * Location: Austin TX, 78758 (Hybrid) * Duration: 11/17/2025 to 11/13/2026 * Team: Fraud ADUS Key Responsibilities: * Develop and ...

Gartner

Director, Data Science

Irving, TX · Remote

Collaborate with engineering, product, UX, and business leaders to prioritize ideas, launch MVPs, iterate rapidly, and deliver measurable business value. * Lead a team of data scientists, driving ...

Gartner

Director, Data Science

Irving, TX · On-site

Collaborate with engineering, product, UX, and business leaders to prioritize ideas, launch MVPs, iterate rapidly, and deliver measurable business value. * Lead a team of data scientists, driving ...

Qorvo, Inc.

Staff Data Science Engineer

Richardson, TX · On-site

Role Summary We are looking for 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 ...

Qorvo, Inc.

Staff Data Science Engineer

Richardson, TX · On-site

Role Summary We are looking for 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 ...

FreedomPay

Data Science Engineer

Austin, TX · On-site

$113K - $136K/yr

FreedomPay is seeking a Data Science Engineer who can creatively solve complex data problems and enhance their product team. The role involves developing machine learning models, collaborating with ...

Qorvo, Inc.

Staff Data Science Engineer

Richardson, TX · On-site

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 ...

Socket.dev

Architect, Data Science

Arlington, TX · On-site

$155 - $190/hr

Data Strategy & Advisory, Data Engineering, Analytics & Visualization, Generative AI & ML, and ... As part of our growing Data Science practice, this role offers an exciting opportunity to lead ...

New

Valero

Data Science Specialist

San Antonio, TX · On-site

Mathematics, Engineering, Data Science or Computer Science or related field or equivalent. * 5 ... years of experience in programing & data mining. * Able and willing to work on-site, in-person at ...

Valero Energy

Data Science Specialist

San Antonio, TX · On-site

Mathematics, Engineering, Data Science or Computer Science or related field or equivalent. * 5+ ... years of experience in programing & data mining. * Able and willing to work on-site, in-person at ...

MD Anderson Center

Senior Data Scientist

Houston, TX · On-site

The ideal candidate has preferred advanced education at the master's or doctoral level in science, engineering, or a related field, along with experience preparing biological data for AI models ...

New

MD Anderson

Senior Data Scientist

Houston, TX · Hybrid

$123K/yr

The ideal candidate has preferred advanced education at the master's or doctoral level in science, engineering, or a related field, along with experience preparing biological data for AI models ...

New

MD Anderson

Senior Data Scientist

Houston, TX · Hybrid

The ideal candidate has preferred advanced education at the master's or doctoral level in science, engineering, or a related field, along with experience preparing biological data for AI models ...

New

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All JobsData Science Developer JobsData Science Developer Jobs in Texas

Data Science Developer information

See Texas salary details

$15

$52

$75

How much do data science developer jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for data science developer in Texas is $52.93, according to ZipRecruiter salary data. Most workers in this role earn between $43.46 and $62.69 per hour, depending on experience, location, and employer.

Is data science highly paid?

Data science developers are generally well-paid due to high demand for skills in statistical analysis, machine learning, and programming languages like Python and R. Salaries vary by experience, location, and industry, but data science roles often offer competitive compensation compared to other tech positions.

What are some common challenges data science developers face when integrating models into production environments?

Data Science Developers often encounter challenges in bridging the gap between developing models in experimental settings and deploying them into scalable, reliable production systems. Issues such as data inconsistencies, version control, and ensuring model reproducibility can arise. Additionally, collaborating effectively with DevOps and engineering teams to automate deployment pipelines and monitor model performance is crucial for long-term success. Understanding both machine learning and software engineering best practices helps overcome these hurdles and ensures smooth, efficient integration.

What is a data science developer?

A Data Science Developer is a professional who combines expertise in programming, statistics, and data analysis to build models and algorithms that extract insights from large datasets. They often work with machine learning techniques, data visualization, and various data processing tools to solve business problems. Data Science Developers collaborate with other teams to design and implement data-driven solutions, and are skilled in languages like Python, R, or Scala. Their work is essential for organizations looking to leverage data for decision-making and innovation.

What are the key skills and qualifications needed to thrive as a data science developer, and why are they important?

To thrive as a Data Science Developer, you need strong expertise in statistics, machine learning, programming (Python, R), and a background in computer science or a related quantitative field. Familiarity with data analysis tools (such as Pandas, NumPy, and scikit-learn), cloud platforms (like AWS or Azure), and experience with databases (SQL/NoSQL) are typically required, and certifications like Microsoft Certified: Azure Data Scientist Associate can be beneficial. Strong problem-solving skills, effective communication, and the ability to collaborate with cross-functional teams help you stand out. These skills are essential for building data-driven solutions that translate complex data into actionable business insights.

Is data science hard to learn?

Data science is a complex field that requires learning skills in programming, statistics, and data analysis, which can be challenging for beginners. Success often depends on prior knowledge, dedication, and practice with tools like Python or R, as well as understanding data concepts. While it can be difficult initially, consistent effort and training can make it manageable for many learners.

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

AspectData Science DeveloperData Analyst
Required SkillsProgramming, machine learning, data modelingData visualization, statistical analysis, reporting
CertificationsData Science certifications, Python/R expertiseExcel, SQL, Tableau certifications
Work EnvironmentTech companies, startups, R&D teamsBusiness departments, marketing, finance
Job FocusDeveloping algorithms, predictive modelsInterpreting data, generating reports

While both roles analyze data, Data Science Developers focus on building models and algorithms to solve complex problems, often requiring programming and machine learning skills. Data Analysts primarily interpret existing data sets to generate insights and reports for business decisions. The roles overlap in data handling but differ in technical depth and objectives.

Is data science a growing career?

Data science is a rapidly expanding field with increasing demand for professionals skilled in statistical analysis, machine learning, and data visualization. As organizations rely more on data-driven decision-making, roles like data science developers are expected to grow significantly in the coming years.
What are popular job titles related to Data Science Developer jobs in Texas? For Data Science Developer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Science Developer jobs in Texas look for? The top searched job categories for Data Science Developer jobs in Texas are:
Data Science Developer jobs near you
Infographic showing various Data Science Developer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $110,094 per year, or $52.9 per hour.

Devops Engineer-BI /Data Science

NAVA Software Solutions

Spring, TX • On-site

$48.50 - $66.50/hr

Full-time

Posted 18 days ago

Job description

NAVA Software solutions is looking for a Devops Engineer - BI /Data Science
Details:
Analytics DevOps Engineer
Location: Spring TX - Hybrid 3 days a week
Duration: 6-12 months
The BI/Data Science DevOps Engineer will be responsible for building and maintaining the CI/CD pipelines, deployment automation, and platform infrastructure that support the organization's Power BI, data science, and analytics ecosystem. This role bridges traditional DevOps practices with the specific needs of BI and ML environments - managing release processes for Power BI content, Databricks workspaces, and data science model deployments. The BI/Data Science DevOps Engineer takes complete ownership of deployment reliability, environment consistency, and operational governance across the analytics platform.
Job Duties/Roles
  • Design, build, and maintain CI/CD pipelines for Power BI reports/datasets, Databricks notebooks/jobs, and ML model deployments across dev, test, and production environments.
  • Automate deployment of Power BI workspaces, datasets, and dataflows using Power BI REST APIs, deployment pipelines, and source-controlled artifacts.
  • Manage Databricks infrastructure-as-code (clusters, jobs, workflows, Unity Catalog objects) using tools such as Terraform, Databricks Asset Bundles, or equivalent.
  • Establish and enforce version control practices (Git-based workflows) for BI artifacts, notebooks, and ML code across teams.
  • Build monitoring, alerting, and logging for pipeline health, job failures, deployment errors, and platform performance across the BI/data science stack.
  • Standardize environment promotion processes (dev → test → prod) with appropriate approval gates, testing, and rollback procedures.
  • Collaborate with Data Science and BI teams to containerize and package models/reports for repeatable, automated deployment.
  • Act as the liaison between Data Science, BI, Data Engineering, and Infrastructure/IT teams to align deployment practices with enterprise standards.
  • Manage access provisioning, secrets, and credentials across environments using secure vaults and role-based access controls.
  • Support cost governance and resource optimization by tracking compute usage, autoscaling policies, and cluster configurations.
  • Troubleshoot deployment failures, environment drift, and integration issues across the analytics and data science toolchain.
  • Document deployment architecture, runbooks, and standard operating procedures for platform reliability and knowledge continuity.

Knowledge, Skills, and Abilities Required (KSAR)
  • Highly proficient in CI/CD tooling such as Azure DevOps, GitHub Actions, or Jenkins.
  • Highly proficient in scripting and automation (PowerShell, Python, Bash) for deployment workflows.
  • Strong working knowledge of the Power BI platform, including deployment pipelines, REST APIs, and workspace/app management.
  • Strong experience with Databricks, including Databricks Asset Bundles, workflows, cluster policies, and Unity Catalog administration.
  • Experience with infrastructure-as-code tools such as Terraform or ARM/Bicep templates.
  • Proficient in Azure suite services relevant to data platforms - Azure Data Factory, Azure Data Lake, Azure Key Vault, Azure Synapse.
  • Solid understanding of Git-based version control and branching strategies for analytics and ML artifacts.
  • Familiarity with containerization and orchestration concepts (Docker, Kubernetes) as applied to model/report deployment.
  • Understanding of MLOps concepts - model versioning, monitoring, and automated retraining/deployment pipelines - is a strong plus.
  • Excellent verbal, written, and presentation skills, able to translate technical deployment concepts to non-technical stakeholders.
  • Attentive to detail, with strong troubleshooting and root-cause analysis skills.
  • Ability to manage highly confidential material and enforce security/compliance standards.

Minimum Years of Experience
Typically, 5 or more years of experience in DevOps, platform engineering, or infrastructure roles, with at least 2 years focused on BI or data science/ML deployment environments.
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About NAVA Software Solutions

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NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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