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Statistical Programming Jobs in Virginia (NOW HIRING)

Programming Languages: Experience with statistical programming languages such as Python (using libraries like Pandas, NumPy, and Matplotlib) or R for complex analysis and automation. Data ...

Experience with statistical programming languages such as Python (using libraries like Pandas, NumPy, and Matplotlib) or R for complex analysis and automation. • Data Visualization Tools: Hands-on ...

S.-based company, BWXT is a Fortune 1000 and Defense News Top 100 manufacturing and engineering ... Perform statistical evaluations of quality assurance data using exploratory data analysis ...

S.-based company, BWXT is a Fortune 1000 and Defense News Top 100 manufacturing and engineering ... Perform statistical evaluations of quality assurance data using exploratory data analysis ...

Statistician

Lynchburg, VA · On-site

$66K - $101K/yr

S.-based company, BWXT is a Fortune 1000 and Defense News Top 100 manufacturing and engineering ... Perform statistical evaluations of quality assurance data using exploratory data analysis ...

Statistician/Mathematician

Herndon, VA · On-site

$112K - $179K/yr

Process large amounts of data for statistical modeling and graphic analysis/ metrics. * Develop software or work with developers to automate the collecting and processing of data. * Produce the ...

Statistician/Mathematician

Reston, VA · On-site

$112K - $179K/yr

Process large amounts of data for statistical modeling and graphic analysis/ metrics. * Develop software or work with developers to automate the collecting and processing of data. * Produce the ...

Statistician/Mathematician

Herndon, VA · On-site

$112K - $179K/yr

Process large amounts of data for statistical modeling and graphic analysis/ metrics. * Develop software or work with developers to automate the collecting and processing of data. * Produce the ...

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Statistical Programming information

See Virginia salary details

$83.8K

$146K

$246.9K

How much do statistical programming jobs pay per year?

As of May 29, 2026, the average yearly pay for statistical programming in Virginia is $146,028.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,900.00 and $158,600.00 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 the most commonly searched types of Statistical Programming jobs in Virginia? The most popular types of Statistical Programming jobs in Virginia are:
What are popular job titles related to Statistical Programming jobs in Virginia? For Statistical Programming jobs in Virginia, the most frequently searched job titles are:

Other

Posted 9 days ago


Job description

TLA is seeking a detail-oriented and analytical Data Analyst to transform complex data sets into actionable business insights. The ideal candidate will be responsible for the full lifecycle of data analysis, including data collection, cleaning, interpretation, and presentation of findings to stakeholders to drive strategic decision-making across the organization.

Key Responsibilities:

  • Data Collection & Management: Collect data from primary and secondary sources, and maintain databases and data systems to ensure accuracy and integrity.
  • Data Cleaning & Preparation: Clean, filter, and transform raw data to remove inconsistencies and prepare it for analysis, ensuring high data quality.
  • Statistical Analysis: Apply appropriate statistical methods and techniques to interpret data, analyze trends, and identify patterns and correlations that provide valuable business insights.
  • Reporting & Visualization: Develop and maintain reports, interactive dashboards, and Key Performance Indicators (KPIs) using data visualization tools to communicate findings in an understandable format for non-technical stakeholders.
  • Problem Solving: Collaborate with cross-functional teams (e.g., Marketing, Finance, Operations) to understand business requirements, define analytical needs, and provide data-driven recommendations to solve complex problems and improve processes.
  • Documentation: Create clear and concise documentation of data sources, analysis processes, and results to ensure reproducibility and transparency.
  • Process Improvement: Identify and implement opportunities to automate and streamline data collection and reporting processes for improved efficiency.

Required Skills and Experience:

         Proficiency in SQL: Essential for querying and managing data in relational databases, including advanced functions like joins and aggregations.

         Strong Excel Skills: Advanced proficiency with spreadsheet software, including pivot tables, VLOOKUP/INDEX-MATCH, and complex formulas for data manipulation and quick analysis.

         Programming Languages: Experience with statistical programming languages such as Python (using libraries like Pandas, NumPy, and Matplotlib) or R for complex analysis and automation.

         Data Visualization Tools: Hands-on experience with Business Intelligence (BI) and data visualization platforms (Tableau or Microsoft Power BI preferred).

         Statistical Knowledge: Solid understanding of statistical concepts, including hypothesis testing, regression analysis, and A/B testing.

Soft Skills

         Analytical and Critical Thinking: The ability to logically approach complex problems, ask the right questions, and evaluate data objectively.

         Communication Skills: Excellent written and verbal communication skills, with the ability to translate technical findings into clear, compelling narratives for diverse audiences.

         Attention to Detail: Meticulous attention to detail to ensure the accuracy and reliability of data and analysis.

         Problem-Solving Abilities: A proactive mindset to troubleshoot data issues and find innovative solutions.

         Collaboration: Strong interpersonal skills and the ability to work effectively within a team environment and with various stakeholders.

Experience and Education

Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, or a related discipline.

Preferred Certifications and Qualifications:

While not required, the following certifications are a plus:

         Microsoft Certified: Power BI Data Analyst Associate

         Google Data Analytics Professional Certificate

         Certified Analytics Professional (CAP)

AWS Certified Data Analytics - Specialty (for roles involving cloud platforms)

Requirements

Preferred Certifications and Qualifications:

While not required, the following certifications are a plus:

         Microsoft Certified: Power BI Data Analyst Associate

         Google Data Analytics Professional Certificate

         Certified Analytics Professional (CAP)

AWS Certified Data Analytics - Specialty (for roles involving cloud platforms)