... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
... data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality ...
Statistical Analysis Data Reconfiguration information
See New York salary details
$32.8K - $41.5K
4% of jobs
$41.5K - $50.2K
13% of jobs
$50.2K - $58.9K
5% of jobs
$61.3K is the 25th percentile. Wages below this are outliers.
$58.9K - $67.6K
10% of jobs
The median wage is $73.8K / yr.
$67.6K - $76.3K
26% of jobs
$76.3K - $85K
17% of jobs
$85.4K is the 75th percentile. Wages above this are outliers.
$85K - $93.7K
12% of jobs
$93.7K - $102.4K
6% of jobs
$102.4K - $111.1K
2% of jobs
$111.1K - $119.8K
3% of jobs
$119.8K - $128.6K
2% of jobs
$32.8K
$77.1K
$128.6K
How much do statistical analysis data reconfiguration jobs pay per year?
As of Aug 22, 2026, the average yearly pay for statistical analysis data reconfiguration in New York is $77,075.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $88,600.00 per year, depending on experience, location, and employer.
What is the difference between Statistical Analysis Data Reconfiguration vs Data Analyst?
| Aspect | Statistical Analysis Data Reconfiguration | Data Analyst |
|---|---|---|
| Primary Focus | Rearranging and transforming data sets for analysis readiness | Interpreting data to generate reports and insights |
| Skills & Certifications | Statistical software, data manipulation, certifications like CAP or SAS | Data visualization, SQL, Excel, often with a bachelor's degree in related fields |
| Work Environment | Data processing teams, research labs, analytics departments | Business units, marketing, finance, or operations teams |
While both roles involve working with data, Statistical Analysis Data Reconfiguration specializes in preparing and transforming data for analysis, whereas Data Analysts focus on interpreting data to produce reports and insights. Understanding these differences helps organizations assign the right skills to each role.
What are popular job titles related to Statistical Analysis Data Reconfiguration jobs in New York?
For Statistical Analysis Data Reconfiguration jobs in New York, the most frequently searched job titles are:
- Director Baseball Data Analyst
- Entry Level Financial Data Analyst
- Afternoon Mis Data Analyst
- Evening H1B Visa Sponsorship Data Analyst
- Work From Home Music Data Analyst
- Entry Level Economic Data Analyst
- Data Analyst Internship Sql
- Online Quality Analyst
- Night Shift Dashboard Reporting Analyst
- Remote Social Data Analyst
What job categories do people searching Statistical Analysis Data Reconfiguration jobs in New York look for?
The top searched job categories for Statistical Analysis Data Reconfiguration jobs in New York are:
What cities in New York are hiring for Statistical Analysis Data Reconfiguration jobs?
Cities in New York with the most Statistical Analysis Data Reconfiguration job openings:
Full-time
Posted 10 days ago
Job description
We are seeking a Senior Statistical Analyst with strong expertise in SAS and R programming, CDISC standards, and clinical trial data analysis. The ideal candidate will collaborate with statisticians and cross-functional teams to develop ADaM datasets, generate TLFs, support regulatory submissions, and ensure high-quality statistical programming deliverables for clinical studies.
Primary Responsibilities
*Collaborate with statisticians to develop and implement Statistical Programming Plans (SPPs) and Statistical Analysis Plans (SAPs).
*Program, validate, and maintain ADaM datasets, statistical analyses, and programming deliverables using SAS and R.
*Generate and validate Tables, Listings, and Figures (TLFs) for clinical study reports, safety reports, and regulatory submissions.
*Create and maintain programming documentation, including specifications, annotated code, validation plans, and programming guidelines.
*Perform quality control and validation of statistical programming outputs to ensure compliance with CDISC standards and regulatory requirements.
*Support ad hoc statistical analyses, exploratory data analyses, and data visualization requests.
*Develop and maintain reusable programming macros, utilities, and automation tools to improve efficiency and consistency.
*Provide programming support during regulatory submissions, audits, and inspections.
*Collaborate with study teams to resolve programming and data-related issues while ensuring timely project delivery.
*Identify project risks, escalate issues when necessary, and provide regular status updates.
*Mentor and train junior programmers and contribute to continuous process improvement initiatives.
*Stay current with industry best practices, regulatory guidelines, and advancements in statistical programming.
Required Skills & Qualifications
*Strong proficiency in SAS and R programming for clinical trial data analysis.
*Experience programming and validating ADaM datasets, TLFs, and statistical analyses.
*Advanced knowledge of CDISC standards, including ADaM and SDTM.
*Solid understanding of clinical trial processes, statistical methodologies, and regulatory requirements.
*Experience in therapeutic areas such as Oncology, Immunology, Neuroscience, or other clinical domains.
*Strong analytical, troubleshooting, and problem-solving skills.
*Excellent attention to detail with a strong focus on quality and compliance.
*Effective written and verbal communication skills.
*Ability to collaborate with statisticians, clinical study teams, and external stakeholders.
*Proven ability to manage multiple priorities and meet project deadlines in a fast-paced environment.
Preferred Qualifications
*Experience supporting global clinical trials and regulatory submissions.
*Knowledge of clinical data visualization and exploratory data analysis.
*Experience developing standardized SAS macros and programming utilities.
*Prior experience mentoring or leading statistical programming teams.
*Familiarity with FDA, EMA, and ICH regulatory guidelines for clinical data submissions.