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Statistical Programming Jobs in Virginia (NOW HIRING)

TLA-LLC

Data Analyst

Mclean, VA · On-site

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 ...

TLA-LLC

Data Analyst

Mclean, VA

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 ...

Cmu

Senior Cyber Risk Engineer

Arlington, VA

Cybersecurity Risk Engineersat the SEI use advanced skills in statistics, mathematics, risk analysis, systems engineering, economics and other technical fields in an interdisciplinary manner to help ...

BWXT

Statistician

Lynchburg, VA

$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 ...

BWX Technologies, Inc.

Statistician

Lynchburg, VA

$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 ...

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All JobsStatistical Programming JobsStatistical Programming Jobs in Virginia

Statistical Programming information

See Virginia salary details

$83.8K

$146K

$246.9K

How much do statistical programming jobs pay per year?

As of Jul 14, 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 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.

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 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:
Statistical Programming jobs near you
Infographic showing various Statistical Programming job openings in Virginia as of July 2026, with employment types broken down into 1% Internship, 83% Full Time, 12% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $146,028 per year, or $70.2 per hour.

Data Scientist with Security Clearance

Gateway Geospatial Group

Springfield, VA • On-site

Other

Posted 11 days ago

Job description

About the role G3 is looking for a Data Scientist to develop methods for querying, visualizing, aggregating, correlating, and analyzing big data across intelligence disciplines. Optimize databases, expose new datasets, build custom tools, and apply mathematical concepts to solve complex geospatial intelligence analysis problems. Responsibilities * Develop methods for querying, visualizing, aggregating, correlating, and analyzing big data across intel disciplines * Optimize existing databases to speed up the query, input, export and visualization of data * Work with AOS and AOB teams to develop strategies for exposing new datasets and create migration plans for legacy datasets * Build custom solutions (tools, processes, etc.) to automate or assist analytic endeavors as submitted by AOS and AOB leadership and analytic units * Write scripts in Visual Basic, R, Python or other software for statistical models using large datasets to extract patterns, relationships, and anticipatory behaviors that are repeatable, efficient, and enable hypothesis testing and knowledge capture * Use mathematical concepts and techniques to solve complex GEOINT analysis problems * Utilize ArcGIS, Excel, SPSS, SAS, MATLAB, R and other statistical packages to analyze and visualize operational data * Visualize data both temporally and spatially to assist in data integrity checks, prepare follow-on analysis, ask the next question, and display analytical assessments * Maintain, move and manipulate data between applications using SQL databases, ArcServer, table data, relational/NoSQL DBMS, Excel, Access, Tableau, Insights, Oracle * Develop tradecraft techniques and training solutions for discovery, preparation, manipulation and normalization of big data so that methods are repeatable and can be explained to users Required qualifications * Active TS/SCI security clearance * Bachelor's degree in Computer Science, Mathematics, Statistics, or related technical field required; Master's degree preferred * 3+ years of experience in data science, data analysis, or related field * Strong proficiency in SQL and relational database concepts * Experience with statistical programming languages such as R, Python, MATLAB * Knowledge of geospatial analysis concepts and tools such as ArcGIS * Familiarity with big data technologies like Hadoop, Spark, NoSQL databases * Excellent problem-solving skills and ability to develop innovative solutions * Strong verbal and written communication skills Preferred qualifications * 5+ years of experience in data science, preferably in the intelligence community * Experience working with geospatial intelligence data and products * Knowledge of NGA's mission, organization, and functions * Familiarity with IC data sources, tools, and analytic methodologies * Experience developing and deploying machine learning models * Ability to collaborate effectively in cross-functional teams * Strong leadership skills and ability to mentor junior analysts

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