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Assistant R Statistical Programmer Jobs in Ashburn, VA

Remote micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a ... Proficiency in SAS and/or R, with the ability to independently reproduce analyses from written ...

Advanced skill in Python and R * Advanced skill in SQL and querying (able to pull/transform your ... Doctoral degree in Statistics, Mathematics, Computer Science, Engineering or another quantitative ...

Background in statistical programming language (ideally SPSS, R, Tableau). Do you have what it takes? * Top Secret clearance with poly. * Master's degree with 6-10 years of expereince or Bachelor ...

Showing results 21-40

Assistant R Statistical Programmer information

See Ashburn, VA salary details

$86.4K

$150.6K

$254.6K

How much do assistant r statistical programmer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for assistant r statistical programmer in Ashburn, VA is $150,621.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,800.00 and $163,600.00 per year, depending on experience, location, and employer.

What is the difference between Assistant R Statistical Programmer vs Data Analyst?

AspectAssistant R Statistical ProgrammerData Analyst
Required SkillsProficiency in R, basic statistical knowledge, programming skillsData manipulation, visualization, statistical analysis, often using R or Excel
Work EnvironmentClinical research, pharmaceutical, or biotech industriesBusiness, marketing, finance, healthcare sectors
CertificationsOften requires a degree in statistics, biostatistics, or related fieldsDegree in statistics, data science, or related fields; certifications like CAP or Microsoft certifications are common

While both roles involve data analysis and programming skills, the Assistant R Statistical Programmer primarily supports clinical trials and pharmaceutical research, focusing on statistical programming in R. Data Analysts work across various industries analyzing data to inform business decisions. The roles share similar educational backgrounds but differ in industry focus and specific job functions.

Are Assistant R Statistical Programmers in demand?

Assistant R Statistical Programmers are in demand due to the growing need for data analysis and statistical programming in industries like healthcare, finance, and research. Proficiency in R, along with knowledge of clinical trial processes and statistical methods, enhances job prospects in this field.

What are popular job titles related to Assistant R Statistical Programmer jobs in Ashburn, VA?

For Assistant R Statistical Programmer jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Assistant R Statistical Programmer jobs in Ashburn, VA look for?

The top searched job categories for Assistant R Statistical Programmer jobs in Ashburn, VA are:

What cities near Ashburn, VA are hiring for Assistant R Statistical Programmer jobs?

Cities near Ashburn, VA with the most Assistant R Statistical Programmer job openings:

Infographic showing various Assistant R Statistical Programmer job openings in Ashburn, VA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $150,621 per year, or $72.4 per hour.

Senior Data Scientist -- Data Quality & Statistical Methodology

Mclean, VA • On-site

Other

Medical, Dental, Vision

Re-posted yesterday


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.

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