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Entry Level Statistical Programmer Jobs in Texas

Strike

AI Analyst I

Spring, TX · On-site

This entry-level role is ideal for candidates with a strong analytical foundation who are eager to ... Bachelor's degree in Data Science, AI, Statistics, Mathematics, or a related field. * Basic ...

Strike

AI Analyst I

Spring, TX · On-site

This entry-level role is ideal for candidates with a strong analytical foundation who are eager to ... Bachelor's degree in Data Science, AI, Statistics, Mathematics, or a related field. * Basic ...

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Entry Level Statistical Programmer information

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$78.7K

$137.2K

$232K

How much do entry level statistical programmer jobs pay per year?

As of May 29, 2026, the average yearly pay for entry level statistical programmer in Texas is $137,225.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,500.00 and $149,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Entry Level Statistical Programmer, and why are they important?

To thrive as an Entry Level Statistical Programmer, you need a solid understanding of statistics, programming (especially in SAS, R, or Python), and a relevant degree such as in statistics, mathematics, or computer science. Familiarity with data analysis tools, statistical software (like SAS or R), and version control systems is typically required, and SAS certification can be an advantage. Attention to detail, problem-solving ability, and effective communication are valuable soft skills for this role. These skills and qualities are crucial for accurate data analysis, efficient collaboration, and producing reliable results in data-driven environments.

What are some common challenges faced by entry level statistical programmers when transitioning from academic projects to real-world clinical trial data?

Entry level statistical programmers often find the transition to industry challenging due to the complexity of real-world clinical trial data, strict regulatory requirements, and the need to adhere to standardized processes like CDISC. Unlike academic projects, the work environment emphasizes collaboration with statisticians, data managers, and clinical teams, making communication and teamwork vital. Additionally, maintaining high-quality documentation and learning to use industry-specific tools and programming standards are crucial for success. Seeking mentorship and being proactive in learning these processes can help new programmers adapt more quickly.

What does an Entry Level Statistical Programmer do?

An Entry Level Statistical Programmer assists in analyzing data using statistical software, such as SAS or R, primarily in industries like pharmaceuticals, healthcare, or research. They are responsible for coding, cleaning, and organizing datasets, generating tables, listings, and figures, and ensuring data accuracy. These programmers work closely with statisticians and data managers to support clinical trials or research projects. The role serves as a foundation for more advanced programming and data analysis positions.

What is the difference between Entry Level Statistical Programmer vs Data Analyst?

AspectEntry Level Statistical ProgrammerData Analyst
Required CredentialsBachelor's in Statistics, Biostatistics, or related field; basic programming skills (SAS, R)Bachelor's in Statistics, Data Science, or related field; proficiency in Excel, SQL, and visualization tools
Work EnvironmentPharmaceutical or clinical research settings; focus on data processing and programmingVarious industries including finance, marketing, healthcare; focus on data interpretation and reporting
Employer & Industry UsagePharmaceutical companies, CROs, biotech firmsCorporations, consulting firms, healthcare organizations

While both roles involve working with data, Entry Level Statistical Programmers primarily focus on programming and data management within clinical or research settings, whereas Data Analysts interpret data to inform business decisions across various industries.

What are the most commonly searched types of Statistical Programmer jobs in Texas? The most popular types of Statistical Programmer jobs in Texas are:
What are popular job titles related to Entry Level Statistical Programmer jobs in Texas? For Entry Level Statistical Programmer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Entry Level Statistical Programmer jobs in Texas look for? The top searched job categories for Entry Level Statistical Programmer jobs in Texas are:
What cities in Texas are hiring for Entry Level Statistical Programmer jobs? Cities in Texas with the most Entry Level Statistical Programmer job openings:
Entry Level Statistical Programmer jobs near you
Infographic showing various Entry Level Statistical Programmer job openings in Texas as of May 2026, with employment types broken down into 100% Full Time. Highlights an 91% In-person, and 9% Hybrid job distribution, with an average salary of $137,225 per year, or $66 per hour.
Associate Analytics Engineer - Data & Visualization

Associate Analytics Engineer - Data & Visualization

SHI

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 16 days ago

Job description

About Us

Since 1989, SHI International Corp. has helped organizations change the world through technology. We've grown every year since, and today we're proud to be a $16 billion global provider of IT solutions and services.

Over 17,000 organizations worldwide rely on SHI's concierge approach to help them solve what's next.But the heartbeat of SHI is our employees - all 7,000 of them.If you join our team, you'll enjoy:

  • Our commitment to diversity, as the largest minority- and woman-owned enterprise in the U.S.

  • Continuous professional growth and leadership opportunities.

  • Health, wellness, and financial benefits to offer peace of mind to you and your family.

  • World-class facilities and the technology you need to thrive - in our offices or yours.

Job SummaryThe Associate Analytics Engineer - Data & Visualization supports the development, maintenance, and continuous improvement of dashboards, reporting solutions, and data models that enable business teams to make informed, datadriven decisions. This entrylevel role is designed for earlycareer professionals looking to build a strong foundation in analytics engineering, business intelligence, and data visualization within a modern, cloudbased data environment.
Working closely with senior team members, this role helps transform raw data into trusted, actionable insights while learning best practices related to data modeling, dashboard design, governance, and analytics delivery. This position directly supports the newly combined ITAM, FinOps, and MSOS organization, known as Spend Optimization Services (SOS).

Role Description

Dashboard & Visualization Support

  • Support the development and maintenance of dashboards and reports using tools such as Microsoft Power BI

  • Assist with implementing dashboard enhancements, bug fixes, and usability improvements

  • Help ensure dashboards are visually clear, intuitive, and aligned with established reporting standards

  • Validate dashboard data accuracy and support testing activities prior to releases

  • Support recurring reporting and respond to ad hoc data requests from business stakeholders

Data Engineering & Transformation Support

  • Assist in building and maintaining datasets, transformation logic, and curated reporting tables

  • Support data quality validation and troubleshooting across reporting pipelines

  • Learn and apply analytics engineering best practices related to data structures, naming conventions, and governance

  • Help maintain documentation for datasets, business rules, and KPI definitions

  • Support the broader analytics architecture across platforms such as Microsoft Fabric, SQLbased environments, and cloud data platforms

Analytics Operations & Delivery

  • Participate in sprint planning, backlog refinement, and regular status updates

  • Track work and updates using project management tools such as Asana

  • Collaborate with senior analytics engineers and analysts to support project delivery timelines

  • Assist with production support and issue resolution for dashboards and reporting solutions

  • Learn how analytics solutions integrate with enterprise business processes and workflows

What Success Looks Like

  • Produces accurate, reliable, and wellstructured reporting outputs

  • Demonstrates curiosity, initiative, and continuous learning in analytics engineering concepts

  • Contributes positively to team collaboration and delivery goals

  • Builds stronger technical and business understanding over time

  • Develops confidence in independently supporting dashboards, datasets, and reporting workflows


Behaviors and Competencies

  • Analytical Thinking: Can apply critical thinking to analyze data, identify patterns, and make basic inferences.

  • Data Analysis: Can identify patterns and trends in data, propose hypotheses, and use statistical techniques to test them.

  • Data Literacy: Can identify relevant data sources, collect data, and use basic tools to interpret and report findings.

  • Critical Thinking: Can analyze and interpret data to inform decision-making, and propose solutions based on logical reasoning.

  • Attention to Detail: Can identify errors or inconsistencies in work and make necessary corrections.

  • Communication: Can effectively communicate complex ideas and information, and can adapt communication style to the audience.

  • Problem-Solving: Can identify problems, propose solutions, and take action to resolve them without explicit instructions.

  • Technical Expertise: Can apply technical knowledge and skills effectively in most situations, with occasional guidance.

  • Time Management: Can generally use time effectively and is working towards improving task prioritization and deadline management.

  • Continuous Improvement: Can identify moderate areas for improvement and implement moderate changes.


Skill Level Requirements

  • Foundational analytics and data engineering skill set

  • Ability to work with SQL and relational database structures

  • Data visualization and reporting ability

  • Analytical thinking and attention to detail

  • Problemsolving and troubleshooting skills

  • Clear written and verbal communication skills

  • Collaboration skills within crossfunctional technical teams

  • Ability to manage multiple tasks in a structured, sprintbased environment

  • Willingness to learn new technologies and analytics best practices


Other Requirements

  • Bachelor's degree or equivalent experience required

  • 1-2 years of experience in analytics engineering, business intelligence development, or data modeling roles

  • Foundational understanding of SQL and relational databases

  • Exposure to data visualization or reporting tools through coursework, internships, or personal projects

Preferred:

  • Internship, academic, or project experience using Microsoft Power BI or similar business intelligence tools

  • Exposure to technologies such as SQL, Python, PySpark, or cloudbased data platforms

  • Familiarity with analytics concepts such as ETL/ELT, data modeling, or dashboard design

  • Interest in analytics engineering, business intelligence, or data visualization as a longterm career path

The estimated annual pay range for this position is $75,000 - $95,000 which includes a base salary and bonus. The compensation for this position is dependent on job-related knowledge, skills, experience, and market location and, therefore, will vary from individual to individual. Benefits may include, but are not limited to, medical, vision, dental, 401K, and flexible spending.

Equal Employment Opportunity - M/F/Disability/Protected Veteran Status

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