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Full Time Applied Statistics Jobs (NOW HIRING)

krg technology inc

UI Designer

Redmond, WA

Redmond, WA Duration: Full Time 1. Solid portfolio summarizing 5+ years of data/interaction/visual ... analysis and applied statistics a plus Responsibilities: 1. Build layout and design dynamic ...

Huntington Ingalls Industries

$85K - $130K/yr

Requisition Number: 29338 Required Travel: 0 - 10% Employment Type: Full Time/Salaried/Exempt ... Bachelor's degree in engineering, statistics, applied math, operations research, or similar * 5 ...

Cni

Data Analyst III

Natick, MA

$95K - $120K/yr

CNI offers premium benefits eligible on the first day of hire to full time employees; (Medical ... A strong background in health economics, epidemiology, public health, applied statistics, or a ...

Uofl

Belknap Campus Time Type: Full time Worker Type: Regular Term (Fixed Term) Job Req ID: R108765 ... Experience teaching applied statistics, data analysis, and sport analytics within sport science or ...

Sonsoft Inc

Data Scientist

Plano, TX

Good applied statistics skills, such as distributions, statistical testing, regression, etc. * Good ... This is a Full-Time Permanent job opportunity for you. * Only US Citizen, Green Card Holder, TN ...

Weeghman & Briggs LLC

Data Scientist 2

Augusta, GA · On-site

$114K - $127K/yr

TS/SCI with Polygraph Employment Type: Full-Time Salary Range: $114,900-$127,700Join a Growing Team ... Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine ...

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Full Time Applied Statistics information

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How much do full time applied statistics jobs pay per year?

As of Aug 21, 2026, the average yearly pay for full time applied statistics in the United States is $83,657.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,000.00 and $116,000.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Applied Statistics vs Data Analyst?

AspectFull Time Applied StatisticsData Analyst
Required CredentialsBachelor's or Master's in Statistics, Mathematics, or related fieldBachelor's degree in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, industry R&D teamsBusiness, marketing, finance departments
Employer & Industry UsageUniversities, research institutions, tech companiesCorporations, consulting firms, government agencies
Common Search & ComparisonApplied Statistics roles, careers in statisticsData analysis jobs, data visualization roles

Full Time Applied Statistics professionals focus on developing statistical models, conducting research, and applying advanced statistical methods across various industries. Data Analysts typically interpret data, create reports, and support decision-making with data visualization tools. While both roles require strong analytical skills, Applied Statisticians often have more specialized training in statistical theory, whereas Data Analysts focus on data interpretation and presentation.

Is full time applied statistics a good career?

Full-time applied statistics is a strong career choice for those interested in data analysis, modeling, and decision-making across industries such as healthcare, finance, and technology. It typically requires skills in programming, statistical software, and data interpretation, with job prospects often improving with advanced degrees or certifications. The field offers competitive salaries and opportunities for growth as data-driven decision-making becomes increasingly important.

What jobs can you get with full time applied statistics?

A full-time applied statistics degree prepares individuals for roles such as data analyst, statistician, data scientist, operations analyst, and research analyst. These positions typically require skills in statistical software, data interpretation, and problem-solving, often within industries like finance, healthcare, marketing, or technology.

Where can I work with a degree in full time applied statistics?

A degree in full time applied statistics qualifies you for roles such as data analyst, data scientist, quantitative analyst, or research analyst across various industries including finance, healthcare, technology, and government. These positions often require skills in statistical software, programming languages like R or Python, and data visualization tools. Employment can be found in corporate settings, research institutions, consulting firms, and public sector agencies.
More about Full Time Applied Statistics jobs

What are the most commonly searched types of Applied Statistics jobs?

The most popular types of Applied Statistics jobs are:

What job categories do people searching Full Time Applied Statistics jobs look for?

The top searched job categories for Full Time Applied Statistics jobs are:

Full Time Applied Statistics jobs near you
Infographic showing various Full Time Applied Statistics job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $83,657 per year, or $40.2 per hour.

Senior Data Scientist: Statistical Modeling, AI/ML

Aptive

Remote

Full-time

Re-posted 9 days ago

Aptive Environmental rating

5.6

Company rating: 5.6 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

30th of 35 rated pest control companies

Job description

Job Summary
Aptive Resources LLC is seeking an experienced and highly analytical Senior Data Scientist - Statistical Modeling, AI/ML, and Data Governance to support the Department of Veterans Affairs (VA) Electronic Health Record (EHR) program. This full-time role will support advanced statistical modeling, machine learning and AI evaluation, data governance, data quality assurance, operational analytics, and executive decision support for complex VA healthcare and EHR modernization efforts.
This is a hands-on senior data science position, ideal for someone who combines deep theoretical statistical and mathematical expertise with practical experience improving healthcare data operations. The ideal candidate can evaluate when statistical, AI, or machine learning approaches are appropriate, diagnose when models or reports are not performing as expected, identify data quality and process problems, and build reproducible analytics products using R, SQL, Python, Git, GitHub, and modern cloud/data platforms.
Primary Responsibilities
  • Lead statistical modeling, AI/ML evaluation, and analytic decision support for VA EHR modernization, operational reporting, and executive-facing analytics workstreams.
  • Design, evaluate, and explain statistical and machine learning models, including distributional assumptions, matrix-based methods, dimension reduction, clustering, NLP, simulation, time-series modeling, Bayesian methods, and model limitations.
  • Assess model quality, reliability, bias, drift, and operational usefulness; identify when an analytical approach is not statistically valid or is not appropriate for the available data.
  • Serve as a data governance and data quality assurance point of contact, proactively identifying defects, gaps, anomalies, reporting inconsistencies, data capture issues, and root causes across complex datasets and reporting processes.
  • Develop, maintain, and document reproducible R-based analytics, R packages, scripts, pipelines, dashboards, and governed reporting outputs.
  • Integrate and validate data from enterprise healthcare, operational, EHR, ServiceNow, Corporate Data Warehouse (CDW), Databricks/Azure, and other data sources to support reliable program reporting.
  • Translate stakeholder questions into actionable metrics, KPI definitions, data validation rules, dashboard requirements, quality checks, and recurring reporting products for PMO, functional, and executive audiences.
  • Advise on data governance, provenance, metadata, versioning, access control, code review, documentation, and production standards for analytics teams.
  • Use Git/GitHub and documentation workflows to support version control, collaborative development, pull requests, code review, reproducibility, and transparent analytical delivery.
  • Partner with analysts, data engineers, program managers, and VA stakeholders to move ad hoc analyses into governed, repeatable, auditable data products and reporting processes.
  • Support Agile/SAFe delivery by helping define features, user stories, acceptance criteria, sprint-ready analytics work, and backlog priorities.

Minimum Qualifications
  • 5+ years of applied data science, statistics, machine learning, health informatics, data engineering, or analytics experience in complex enterprise or healthcare environments; federal health, VA, or VHA experience strongly preferred.
  • Advanced degree or equivalent experience in statistics, biostatistics, mathematics, data science, computer science, public health, health informatics, or a related quantitative field.
  • Strong theoretical and applied statistics foundation, including statistical distributions, mathematical modeling, matrix/linear algebra concepts, inference, uncertainty, and model diagnostics.
  • Demonstrated AI/ML experience with the ability to evaluate when models are appropriate and reliable, and to diagnose conditions under which models underperform, drift, become biased, or fail.
  • Advanced proficiency in R for statistical computing, modeling, reproducible analytics, and package/tool development; experience developing or maintaining R packages is strongly valued.
  • Strong SQL skills for querying, joining, validating, and transforming large datasets; working knowledge of Python preferred.
  • Hands-on experience with Git and GitHub for version control, collaboration, code review, and reproducible delivery.
  • Experience supporting data governance, data quality assurance, stewardship, metadata, lineage, provenance, versioning, access control, and analytics documentation.
  • Excellent communication and documentation skills. Able to brief executives, translate technical findings into operational implications, and guide teams toward clean, auditable, compliant analytics.
  • U.S. Citizenship and ability to obtain a Public Trust clearance.

Desired Qualifications
  • Direct experience supporting VA, VHA, VA OIT, Federal EHR modernization, Oracle Cerner/VistA/CPRS transition, or VA enterprise reporting.
  • Experience with Databricks, Azure, Delta tables, Medallion architecture, ServiceNow, Power BI, SAS, Jira, and Confluence.
  • Experience developing executive operational reporting, go-live readiness reporting, issue/configuration tracking, SLA/throughput metrics, or command center decision support.
  • Experience with NLP, document-term matrices, TF-IDF, topic modeling, BERTopic, RAG, prompt engineering, LLM/AI agent evaluation, or knowledge management analytics.
  • Experience creating open-source or internal R packages, style guides, code review frameworks, reusable analytics standards, or production documentation for analytics teams.
  • Ability to work in high-pressure, delivery-critical environments with shifting priorities, ambiguous data, and multiple dependencies.

About Aptive
About Aptive. Aptive partners with federal agencies to achieve their missions through improved performance, streamlined operations and enhanced service delivery. Based in Alexandria, Virginia, we support more than a dozen agencies including Veterans Affairs, Transportation, Defense, Homeland Security and the National Science Foundation. We specialize in applying technology, creativity and human-centered services to optimize mission delivery and improve experiences for millions of people who count on government services every day. Founded: 2012. Employees: 300+ nationwide.
EEO Statement
Aptive is an equal opportunity employer. We consider all qualified applicants for employment without regard to race, color, national origin, religion, creed, sex, sexual orientation, gender identity, marital status, parental status, veteran status, age, disability, or any other protected class. Veterans, members of the Reserve and National Guard, and transitioning active-duty service members are highly encouraged to apply. About Aptive: Aptive partners with federal agencies to achieve their missions through improved performance, streamlined operations and enhanced service delivery. Based in Alexandria, Virginia, we support more than a dozen agencies including Veterans Affairs, Transportation, Defense, Homeland Security and the National Science Foundation. We specialize in applying technology, creativity and human-centered services to optimize mission delivery and improve experiences for millions of people who count on government services every day. Founded: 2012. Employees: 300+ nationwide.

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