1

Sas Statistical Programmer Jobs in Virginia (NOW HIRING)

Director, Biostatistics

Triangle, VA · On-site

$190K - $260K/yr

... Statistical Programmers, Clinical Operations, Data Managers, etc. * Thorough understanding of statistical principles and clinical experiment methodology. * Computational skills using R, and/or SAS ...

Undergraduate Degree in Computer Science, Statistics, Engineering, Economics, Business, Applied ... Basic professional certification with analytics tools (e.g., SAS, R). * Experience with delivery ...

Undergraduate Degree in Computer Science, Statistics, Engineering, Economics, Business, Applied ... Basic professional certification with analytics tools (e.g., SAS, R). * Experience with delivery ...

Public Health Analyst

Vienna, VA · On-site

$57K - $60K/yr

... SAS code known to be valid for creating the variable (e.g., from past cycles or another programmer ... Bachelor's degree in health informatics, public health, statistics, or related field and 6 years of ...

Public Health Analyst

Vienna, VA · On-site +1

$57K - $60K/yr

... SAS code known to be valid for creating the variable (e.g., from past cycles or another programmer ... Bachelor's degree in health informatics, public health, statistics, or related field and 6 years of ...

Scientific Data Analyst

Vienna, VA · On-site

$85K - $115K/yr

... SAS code known to be valid for creating the variable (e.g., from past cycles or another programmer ... Master's degree in public health, statistics, or related field. * Knowledge of public health ...

Data Engineer Mid

Chantilly, VA · On-site

$169K - $179K/yr

Proficiency in statistics packages such as SPSS, SAS, S-PLUS, and R * Programming skills sufficient to extract, transform, and clean multi-terabyte databases * Significant current experience (i.e ...

Showing results 41-60

Sas Statistical Programmer information

See Virginia salary details

$5

$56

$86

How much do sas statistical programmer jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for sas statistical programmer in Virginia is $56.88, according to ZipRecruiter salary data. Most workers in this role earn between $20.96 and $84.62 per hour, depending on experience, location, and employer.

What types of projects do SAS statistical programmers typically work on, and how do they collaborate with other teams?

Sas Statistical Programmers often work on projects involving the analysis and reporting of clinical trial or observational study data, producing datasets, tables, listings, and figures to support regulatory submissions or scientific publications. They routinely collaborate with biostatisticians, clinical data managers, and project managers to ensure data quality and compliance with industry standards. Daily responsibilities include coding in SAS, validating datasets, troubleshooting data issues, and preparing documentation. Effective communication and teamwork are essential, as the role frequently involves working in multidisciplinary teams to meet project goals and timelines.

What is a SAS statistical programmer?

A SAS Statistical Programmer is a professional who utilizes SAS software to manage, analyze, and report statistical data, primarily in industries like pharmaceuticals, healthcare, and clinical research. They write and validate programs to generate tables, listings, and figures for clinical trials or other data-driven studies. Their role involves ensuring data accuracy, compliance with regulatory guidelines, and collaboration with statisticians and researchers to support decision-making.

What are the key skills and qualifications needed to thrive as a SAS statistical programmer, and why are they important?

To thrive as a Sas Statistical Programmer, you need a strong background in statistics, programming (especially SAS), and data management, usually supported by a degree in statistics, computer science, or a related field. Familiarity with SAS Base, SAS Macro, and clinical data standards like CDISC, as well as relevant industry certifications, are commonly required. Attention to detail, strong problem-solving abilities, and effective communication skills are valuable soft skills. These competencies ensure accurate data analysis, clear reporting, and successful collaboration within cross-functional teams in fields like healthcare or pharmaceuticals.

What are popular job titles related to Sas Statistical Programmer jobs in Virginia? For Sas Statistical Programmer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Sas Statistical Programmer jobs in Virginia look for? The top searched job categories for Sas Statistical Programmer jobs in Virginia are:
What are popular job titles related to Sas Statistical Programmer jobs in VA? For Sas Statistical Programmer jobs in VA, the most frequently searched job titles are:
Infographic showing various Sas Statistical Programmer job openings in Virginia as of August 2026, with employment types broken down into 2% Internship, 78% Full Time, 16% Part Time, and 4% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $118,309 per year, or $56.9 per hour.

Senior Data Scientist -- Data Quality & Statistical Methodology (McLean)

BLN24

Mclean, VA • On-site

Part-time

Medical, Dental, Vision

This job post has expired today. Applications are no longer accepted.


Job description

Senior Data Scientist — Data Quality & Statistical Methodology

BLN24 is seeking a Senior Data Scientist with a strong statistical-methodology focus to support a large-scale enterprise data and analytics platform modernization effort. This role sits at the intersection of statistical methodology, data‑quality measurement, and large‑scale data engineering — designing the metrics and methods that determine whether an organization’s core data products can be trusted.

A central challenge is completeness: source data is rarely perfect, and values are routinely missing, partial, or unreliable. The ideal candidate understands how external and secondary data sources can be used to responsibly fill those gaps, and can design defensible, statistically sound quality metrics that measure how well the resulting data reflects reality.

The platform’s anticipated foundation involves a modern lakehouse/cloud data architecture handling very large datasets from multiple providers. The successful candidate will help define the quality‑metric framework and gap‑filling methodology for a generation of stakeholders moving off legacy tools and fragmented, manually validated processes.

Key Responsibilities
  • Design, define, and validate data‑quality metrics for very large datasets — not simply reporting numbers, but establishing what each metric means, how it is calculated, and why it is statistically defensible to leadership
  • Develop and document methodology for filling gaps where source data is missing, partial, or unreliable, using external and secondary reference data, including model‑based and imputation approaches
  • Establish benchmarking approaches that compare data products against authoritative historical and modeled reference datasets to detect drift, bias, and anomalies
  • Specify the data the platform must ingest to support quality monitoring, and define the checks that flag when an upstream‑produced data product looks wrong
  • Partner with subject matter experts (SMEs) and stakeholders to translate operational and analytical questions into concrete, measurable quality requirements
  • Work with data engineers to ensure metrics and gap‑filling logic run reliably at scale on very large, multi‑source datasets built on common keys and governed definitions
  • Account for data sensitivity throughout, ensuring appropriate aggregation, access controls, and privacy‑preserving techniques are reflected in any metric or derived data product
  • Document methodology and requirements in structured, reusable formats (e.g., requirements matrices and detailed requirement specifications)
  • Iterate across multiple review cycles with SMEs and fellow methodologists, given the program’s phased, multi‑year rollout
Required Qualifications
  • 5+ years of applied experience in statistical methodology, data quality, or quantitative research roles
  • Demonstrated experience with missing‑data and imputation methods (e.g., model‑based imputation, hot‑deck, sequential regression) for filling incomplete data
  • Experience designing and validating quantitative metrics for decision‑support, including an understanding of bias, variance, and false‑positive/false‑negative trade‑offs
  • Working knowledge of record linkage / entity resolution concepts, sufficient to build sound metrics on top of matched data
  • Experience with very large datasets on distributed‑compute platforms (e.g., Spark‑based / lakehouse environments) and strong SQL
  • Strong proficiency in Python and R
  • Comfort working with regulated or restricted data and the governance constraints that accompany it
  • Strong communication skills and the ability to explain and defend methodology to leadership and non‑technical stakeholders
Preferred Qualifications
  • Master’s or PhD in Statistics, Applied Mathematics, Econometrics, Data Science, or a related quantitative field (a purely software‑focused background is not sufficient for the methodology components of this role)
  • Prior experience supporting large‑scale enterprise data programs or platform modernization efforts
  • Experience using external or secondary data to supplement or complete primary datasets
  • Familiarity with Databricks and modern lakehouse architectures
  • Exposure to privacy‑preserving analytics techniques or working with regulated data
  • Ability to read and reconcile legacy statistical codebases (e.g., SAS) alongside modern Python/R workflows
  • Background in requirements gathering for enterprise data platforms
  • Experience benchmarking estimates against authoritative reference datasets for anomaly or drift detection
Work Environment
  • Contract position supporting a large‑scale enterprise data modernization engagement
  • Collaborative, cross‑functional environment working alongside data engineers, architects, and SMEs
  • Currently in the requirements‑gathering phase of a multi‑year platform build — a strong opportunity to shape long‑term quality‑metric and methodology standards rather than inherit a fixed framework
  • Must be eligible to work with regulated data and to obtain any background check or clearance required by the client
Benefits

BLN24 benefits are game changing. We like our team to play hard and that means they need to be taken care of — physically, financially, and emotionally. We make sure to keep them in the game by giving them access to generous medical, dental, and vision plans.

  • You can join one of the fastest growing companies headquartered in the Washington DC Metro Area. We give you the opportunity to work in different sectors, so you have the chance at variety while maintaining stability.
  • Flexibility at BLN24 allows each individual the opportunity to balance quality work and their personal lives. Depending on projects, we allow remote working opportunities so you can always be in the game no matter where you call home.

BLN24 is an Equal Opportunity Employer. We believe people are our strength and understand diverse talents are key to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. In accordance with applicable law, we make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as any mental health or physical disability needs.

#J-18808-Ljbffr