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Statistical Programming Jobs in Arkansas (NOW HIRING)

Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Masters: Business Administration, Masters: Information Systems ...

Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Masters: Business Administration, Masters: Information Systems ...

Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Masters: Business Administration, Masters: Information Systems ...

Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Masters: Business Administration, Masters: Information Systems ...

Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Masters: Business Administration, Masters: Information Systems ...

Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Masters: Business Administration, Masters: Information Systems ...

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Statistical Programming information

See Arkansas salary details

$69.9K

$121.8K

$205.9K

How much do statistical programming jobs pay per year?

As of May 31, 2026, the average yearly pay for statistical programming in Arkansas is $121,796.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,400.00 and $132,300.00 per year, depending on experience, location, and employer.

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

To thrive as a Statistical Programmer, you need strong expertise in statistics, programming languages like SAS or R, and a background in mathematics or computer science. Familiarity with statistical software, clinical data management systems, and regulatory standards such as CDISC is typically required. Attention to detail, problem-solving abilities, and effective communication are vital soft skills for collaborating with cross-functional teams. These skills ensure accurate data analysis, regulatory compliance, and successful project delivery in data-driven environments.

What are some common challenges faced by statistical programmers when collaborating with cross-functional teams in clinical research?

Statistical programmers in clinical research often work closely with biostatisticians, data managers, and clinical teams. A common challenge is ensuring clear communication regarding data requirements, analysis specifications, and timelines, as different teams may have varying priorities and technical backgrounds. Navigating frequent changes in study protocols or data standards can also require adaptability and strong project management skills. Building collaborative relationships and maintaining thorough documentation are key to overcoming these challenges and ensuring high-quality, reproducible results.

What is statistical programming?

Statistical programming involves using software tools and programming languages, such as R, SAS, or Python, to manage, analyze, and interpret large sets of data. Professionals in this field write code to perform statistical analyses, create data visualizations, and automate data processing tasks. Statistical programming is widely used in industries like pharmaceuticals, finance, public health, and research to support data-driven decision-making and ensure accurate results.

Is SAS programming in demand?

SAS programming is in demand in industries such as healthcare, finance, and pharmaceuticals, especially for data analysis and reporting roles. Many organizations seek professionals skilled in SAS, along with knowledge of statistical methods and data management, making it a valuable skill in the job market for statistical programmers.

What is the difference between Statistical Programming vs Data Analysis?

AspectStatistical ProgrammingData Analysis
Primary FocusDeveloping and implementing statistical models and algorithmsInterpreting data to identify trends and insights
Skills & ToolsProgramming languages (SAS, R, Python), statistical methodsData visualization, descriptive statistics, Excel, SQL
Work EnvironmentPharmaceutical, biotech, or research settingsBusiness, marketing, healthcare sectors
CertificationsOften requires statistical or programming certificationsMay include data analysis or business analytics certifications

While both roles involve working with data, Statistical Programming primarily focuses on creating statistical models and algorithms using programming languages, often in research or clinical settings. Data Analysis emphasizes interpreting data to generate insights for decision-making across various industries. Understanding these differences helps professionals choose the right career path or job focus.

What are popular job titles related to Statistical Programming jobs in Arkansas? For Statistical Programming jobs in Arkansas, the most frequently searched job titles are:
What job categories do people searching Statistical Programming jobs in Arkansas look for? The top searched job categories for Statistical Programming jobs in Arkansas are:
Infographic showing various Statistical Programming job openings in Arkansas as of May 2026, with employment types broken down into 1% As Needed, 75% Full Time, 11% Part Time, 2% Temporary, 10% Contract, and 1% Nights. Highlights an 82% Physical, 8% Hybrid, and 10% Remote job distribution, with an average salary of $121,796 per year, or $58.6 per hour.
Data Scientist I

Data Scientist I

Murphy USA

El Dorado, AR • On-site

Other

Posted 12 days ago


Murphy USA rating

4.2

Company rating: 4.2 out of 10

Based on 248 frontline employees who took The Breakroom Quiz

41st of 47 rated convenience stores


Job description

GENERAL DESCRIPTION OF POSITION
The Data Scientist is responsible for supporting data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role applies industry-leading analytical methodologies for working with large datasets to extract meaningful business insight and creatively solve business problems. Data Scientists are also responsible for ensuring that developed codes are documented into a library of reusable algorithms.
As a Data Scientist, you will apply advanced analytics methods and algorithms for identifying trends and providing business solutions. This role is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships, and focus on understanding the overall business area being supported.
This role will facilitate the end-to-end development, testing, and monitoring of analytical models across our brands. The Data Scientist will use machine learning and algorithms in an effort to improve data quality and generate insights from the data. The role will be very hands-on and focused in AI/ML model development. This scientist will attend daily standups and work in an Agile environment.
ESSENTIAL DUTIES AND RESPONSIBILITIES
- Design and develop algorithms and models to use against large datasets to create business insights
- Participate in analytical projects as a data science/technical lead
- May work independently in a solution environment
- Aid in the appropriate selection, utilization and interpretation of advanced analytical methodologies
- Execute tasks with high levels of efficiency and quality
- Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners including preparing reports, updates and/or presentations related to progress made on a project or solution
- Work with project teams and business partners to determine project goals and deliver productionized models and tools using Agile (including data processing, scripting, modeling, measurement, error handling, and documentation)
- Present recommendations in a confident manner in order to influence execution of recommendation
- Incorporate business knowledge into solution approachIdentify relevant data sources to mine given target outcomes
- Collect large structured and unstructured datasets and variables
- Analyze data for trends and patterns, and interpret data with a clear objective in mind
- Effectively develop trust and collaboration with internal customers and cross-functional teams
- Work with project teams and business partners to determine project goals
- Participate in the continuous improvement of analytics by developing replicable solutions (e.g., codified data products, project documentation, flowcharts) to ensure solutions are leveraged for future projects
- Utilizing statistical techniques to identify key insights that help solve business problems including mastery in predictive modeling, data mining and data analysis
- Perform any other related duties as required or assigned.
QUALIFICATIONS
To perform this job successfully, an individual must be able to perform each essential duty mentioned satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required.
EDUCATION AND EXPERIENCE
Bachelor's degree in a quantitative field like Computer Science, Statistics, Engineering, Science, or Mathematics. 1 to 3 years of related experience in data mining and analytics, database structure and ETL, predictive modeling, machine learning, and statistical programming languages.

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