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Statistical Modeling Jobs in Washington (NOW HIRING)

Data Scientist

Springfield, VA · On-site

$116K - $210K/yr

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Design, develop, and execute test cases for statistical modeling and analytical software applications. * Collaborate closely with quantitative engineers to investigate and resolve test case failures.

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Data Scientist

Springfield, VA · On-site

$116K - $210K/yr

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Azure Data Architect

Washington, DC · On-site +1

$72.25 - $92.75/hr

Expertise in statistical modeling, machine learning algorithms, and data mining techniques. * Must have strong expertise in the Azure Cloud environment * Strong proficiency in Python or similar ...

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Data Scientist

Springfield, VA · On-site

$116K - $210K/yr

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools. * Extract, transform, integrate, and analyze structured, semi ...

Develop and implement statistical models, predictive analytics, and machine learning algorithms. * Design experiments and evaluate models to ensure accuracy, reliability, and scalability. * Translate ...

Showing results 41-60

Statistical Modeling information

See Washington salary details

$41.3K

$62.7K

$112.1K

How much do statistical modeling jobs pay per year?

As of Sep 11, 2026, the average yearly pay for statistical modeling in Washington is $62,689.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,600.00 and $68,000.00 per year, depending on experience, location, and employer.

What is statistical modeling?

Statistical modeling is the process of using mathematical models and statistical techniques to analyze data, identify patterns, and make predictions or inferences. It involves building models that represent relationships between variables in real-world systems. These models can be used for forecasting, hypothesis testing, and decision-making in various fields such as business, science, and engineering. Statistical modeling helps turn raw data into actionable insights by quantifying uncertainty and highlighting significant trends.

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

To excel as a Statistical Modeler, a solid background in statistics, mathematics, and data analysis—often supported by a degree in a quantitative field—is essential. Proficiency with statistical software such as R, Python, SAS, or SPSS and familiarity with data visualization tools are typically required. Strong problem-solving skills, critical thinking, and effective communication help convey complex findings to non-technical stakeholders. These skills ensure accurate model development, actionable insights, and effective decision-making based on data.

What are some common challenges faced by professionals in statistical modeling roles, and how can they be managed?

Professionals in statistical modeling often encounter challenges such as dealing with incomplete or messy data, selecting the most appropriate modeling techniques, and clearly communicating complex results to non-technical stakeholders. Managing these challenges typically involves collaborating closely with data engineers and domain experts, employing robust data cleaning practices, and staying up-to-date with new statistical methods. Additionally, effective communication skills are essential for translating technical findings into actionable business insights, ensuring that modeling efforts drive real-world impact.

What is the difference between Statistical Modeling vs Data Analyst?

AspectStatistical ModelingData Analyst
Required CredentialsDegree in statistics, mathematics, or related field; proficiency in statistical softwareDegree in data science, statistics, or related; strong analytical skills
Work EnvironmentResearch, academia, or data-driven industries; focus on model developmentBusiness, marketing, or finance; focus on data interpretation and reporting
Employer & Industry UsageUsed in industries requiring predictive models and complex analysisUsed across various industries for data reporting and insights

Statistical Modeling involves creating mathematical models to understand data patterns and make predictions, often requiring advanced statistical knowledge. Data Analysts focus on interpreting data, generating reports, and providing actionable insights. While both roles work with data, Statistical Modeling emphasizes model development, whereas Data Analysts concentrate on data interpretation and presentation.

What do statistical modeling do?

Statistical modeling involves developing mathematical representations of data to analyze and predict patterns or outcomes. Professionals in this field use tools like statistical software and techniques such as regression or hypothesis testing to interpret data and support decision-making across various industries.

What are popular job titles related to Statistical Modeling jobs in Washington?

For Statistical Modeling jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Statistical Modeling jobs in Washington look for?

The top searched job categories for Statistical Modeling jobs in Washington are:

What cities in Washington are hiring for Statistical Modeling jobs?

Cities in Washington with the most Statistical Modeling job openings:

Infographic showing various Statistical Modeling job openings in Washington as of August 2026, with employment types broken down into 82% Full Time, 9% Part Time, 2% Temporary, and 7% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution, with an average salary of $62,689 per year, or $30.1 per hour.

Data Scientist

Springfield, VA • On-site

Leidos
IT Services • 10K+ employees

$116K - $210K/yr

Full-time

Medical, Retirement, PTO

Re-posted 17 days ago


Leidos rating

8.3

Company rating: 8.3 out of 10

Based on 153 frontline employees who took The Breakroom Quiz


Job description

Description

Leidos is actively interviewing for a Data Scientist to join our team in Springfield, VA.

Job Summary

Senior-most technical position responsible for leading the design, development, deployment, and optimization of advanced data science solutions in support of government mission objectives. The Data Scientist serves as a recognized subject matter expert in statistical modeling, machine learning, artificial intelligence, data exploitation, and analytic tradecraft. This role requires on-site support at a government facility and close collaboration with mission operators, analysts, engineers, program leadership, and government stakeholders in secure environments.

Key Responsibilities

  • Lead the development and operationalization of advanced data science, machine learning, and artificial intelligence solutions for mission applications.

  • Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools.

  • Extract, transform, integrate, and analyze structured, semi-structured, and unstructured data from multiple government and mission-relevant sources.

  • Develop and validate machine learning models for classification, regression, clustering, anomaly detection, ranking, recommendation, and pattern discovery.

  • Architect end-to-end analytic workflows, including data ingestion, feature engineering, model training, testing, deployment, monitoring, and lifecycle management.

  • Apply advanced quantitative methods to derive actionable insights from large, complex, and high-value datasets.

  • Collaborate with domain experts, mission analysts, software engineers, and government personnel to translate mission needs into technical solutions.

  • Evaluate model performance, quantify uncertainty, and ensure analytic validity, repeatability, and interpretability.

  • Support data governance, security, compliance, and responsible AI practices within government mission environments.

  • Prepare technical documentation, briefings, reports, white papers, and stakeholder presentations.

  • Advise leadership on data science strategy, analytic methodology, capability gaps, and technology insertion opportunities.

Required Technical Skills

  • Statistical modeling and inference

  • Machine learning and artificial intelligence

  • Predictive analytics and forecasting

  • Data mining and pattern analysis

  • Feature engineering and model evaluation

  • Data wrangling, integration, and transformation

  • Python, R, SQL, and scientific computing libraries

  • Visualization and dashboarding tools

  • Model deployment, monitoring, and lifecycle support

  • Documentation, briefing development, and technical communication

Basic Qualifications

  • Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Physics, or a related quantitative field.

  • Minimum of 12–15 years of relevant professional combined experience in data science, advanced analytics, machine learning, artificial intelligence, or statistical modeling.

  • Demonstrated experience developing and deploying production-grade analytic or machine learning solutions in government, defense, intelligence, or other highly regulated environments.

  • Deep knowledge of statistical inference, probability, experimental design, predictive modeling, and machine learning methods.

  • Strong programming experience in Python, R, SQL, or similar analytic languages.

  • Experience working with large, complex, and potentially disparate datasets in enterprise environments.

  • Familiarity with model validation, explainability, bias assessment, and performance evaluation techniques.

  • Strong written and verbal communication skills with the ability to explain complex technical findings to diverse audiences.

  • Active TS/SCI with ability to be approved for a Poly

Preferred Qualifications

  • Master’s degree or Ph.D. in a relevant quantitative or technical discipline.

  • Experience supporting DoD, IC, DHS, civilian federal agencies, or other government mission environments.

  • Experience with deep learning, natural language processing, computer vision, graph analytics, time series analysis, or reinforcement learning.

  • Familiarity with cloud platforms, MLOps, DevSecOps, and containerized deployment environments.

  • Experience with distributed computing, big data platforms (Spark/Databricks or similar), and workflow orchestration tools.

  • Familiarity with emerging Artificial Intelligence (AI) technologies, tools, and methodologies, with an understanding of their applications, implications, and integration into daily geospatial and intelligence workflows.

  • Knowledge of data architecture, data engineering, and enterprise analytics ecosystems.

  • Experience briefing senior government leadership and mission stakeholders.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:August 27, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:Pay Range $116,350.00 - $210,325.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

About Leidos

Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. Headquartered in Reston, Virginia, with 47,000 global employees, Leidos reported annual revenues of approximately $16.7 billion for the fiscal year ended January 3, 2025. For more information, visit www.Leidos.com.

Pay and Benefits

Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available at www.leidos.com/careers/pay-benefits.

Securing Your Data

Beware of fake employment opportunities using Leidos’ name. Leidos will never ask you to provide payment-related information during any part of the employment application process (i.e., ask you for money), nor will Leidos ever advance money as part of the hiring process (i.e., send you a check or money order before doing any work). Further, Leidos will only communicate with you through emails that are generated by the Leidos.com automated system – never from free commercial services (e.g., Gmail, Yahoo, Hotmail) or via WhatsApp, Telegram, etc. If you received an email purporting to be from Leidos that asks for payment-related information or any other personal information (e.g., about you or your previous employer), and you are concerned about its legitimacy, please make us aware immediately by emailing us at LeidosCareersFraud@leidos.com.

If you believe you are the victim of a scam, contact your local law enforcement and report the incident to the U.S. Federal Trade Commission.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.


What Leidos employees say

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Benefits

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About Leidos

Sourced by ZipRecruiter

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers' success. We empower our teams, contribute to our communities, and operate sustainable practices. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Reston, VA, US

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