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Statistical Analysis Jobs (NOW HIRING)

Collaborate with statisticians to develop and implement Statistical Programming Plans (SPPs) and Statistical Analysis Plans (SAPs). *Program, validate, and maintain ADaM datasets, statistical ...

New

Collaborate with statisticians to develop and implement Statistical Programming Plans (SPPs) and Statistical Analysis Plans (SAPs). *Program, validate, and maintain ADaM datasets, statistical ...

New

Collaborate with statisticians to develop and implement Statistical Programming Plans (SPPs) and Statistical Analysis Plans (SAPs). *Program, validate, and maintain ADaM datasets, statistical ...

NJ · On-site

Collaborate with statisticians to develop and implement Statistical Programming Plans (SPPs) and Statistical Analysis Plans (SAPs). *Program, validate, and maintain ADaM datasets, statistical ...

New

Collaborate with statisticians to develop and implement Statistical Programming Plans (SPPs) and Statistical Analysis Plans (SAPs). *Program, validate, and maintain ADaM datasets, statistical ...

New

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Statistical Analysis information

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$70.5K

$117.5K

How much do statistical analysis jobs pay per year?

As of Aug 17, 2026, the average yearly pay for statistical analysis in the United States is $70,450.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,500.00 and $81,000.00 per year, depending on experience, location, and employer.

How does a statistical analyst typically collaborate with other departments within an organization?

Statistical Analysts regularly work with teams such as marketing, finance, product development, and operations to interpret data and provide actionable insights. They often participate in cross-functional meetings to understand departmental goals and ensure that their analyses align with business objectives. Effective communication of complex statistical findings to non-technical colleagues is a key part of the role, as is adapting analysis techniques to suit different project needs. This collaborative environment fosters both professional growth and a deeper understanding of the broader organization.

What is the difference between Statistical Analysis vs Data Analyst?

AspectStatistical AnalysisData Analyst
Required CredentialsDegree in Statistics, Mathematics, or related field; certifications like SAS or SPSSDegree in Data Science, Statistics, or related; similar certifications often preferred
Work EnvironmentResearch labs, academic institutions, or industries focusing on data modelingBusiness settings, tech companies, or marketing firms analyzing data for insights
Employer & Industry UsageUsed across academia, healthcare, finance for in-depth data modelingCommon in corporate, retail, and tech sectors for reporting and visualization

While both roles involve working with data, Statistical Analysis focuses on developing and applying statistical models to interpret data, often requiring advanced statistical knowledge. Data Analysts primarily interpret data to generate reports and insights for business decisions. Both roles share similar credentials but differ in scope and application.

What is statistical analysis?

Statistical analysis is the process of collecting, exploring, and interpreting large amounts of data to discover underlying patterns and trends. It involves applying mathematical techniques to summarize data, test hypotheses, and make informed decisions. Professionals use statistical analysis in fields like business, healthcare, social sciences, and engineering to support evidence-based conclusions and predict future outcomes. Common methods include descriptive statistics, inferential statistics, regression analysis, and hypothesis testing.

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

To thrive as a Statistical Analyst, you need a solid background in statistics, mathematics, and data analysis, usually supported by a relevant degree such as statistics, mathematics, or data science. Familiarity with statistical software like R, SAS, SPSS, or Python, as well as experience with data visualization tools, is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you interpret and present complex data clearly. These skills ensure that analyses are accurate, actionable, and effectively support decision-making in various industries.
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Cities with the most Statistical Analysis job openings:

What are the most commonly searched types of Statistical Analysis jobs?

The most popular types of Statistical Analysis jobs are:

What states have the most Statistical Analysis jobs?

States with the most job openings for Statistical Analysis jobs include:

Infographic showing various Statistical Analysis job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $70,450 per year, or $33.9 per hour.

Senior Statistical Analyst

2T Consulting

South Richmond Hill, NY

Full-time

Posted 9 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.