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Statistical Modeling Jobs in Seattle, WA (NOW HIRING)

Think Tank, Inc.

Statistician

Seattle, WA

Develop novel probabilistic mathematical and simulation models representing complex ecological and behavioral processes with modern statistical methods. * Provide statistical support to other ...

Ra

Marketing Analytics Manager

Seattle, WA · On-site

Who is proficient in SAS or other statistical modeling tools. Who enjoys traveling, because this role involves traveling (80% to 100%). Who is proficient in Applied Statistics/Econometrics ...

Think Tank, Inc.

Statistician

Seattle, WA · On-site

Develop novel probabilistic mathematical and simulation models representing complex ecological and behavioral processes with modern statistical methods.Provide statistical support to other ...

DevSelect

Principal Data Scientist

Redmond, WA · On-site

Understanding of machine learning techniques including predictive modeling, text and image mining, clustering, deep learning, anomaly detection, forecasting methods and other advanced statistical ...

Amazon

Data Scientist, Prime Video Science

Seattle, WA · On-site

You will work close to science: probing why a model behaves the way it does, pressure-testing results before they reach senior leaders, and, where it helps, building your own statistical and causal ...

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All JobsStatistical Modeling JobsStatistical Modeling Jobs in Seattle, WA

Statistical Modeling information

See Seattle, WA salary details

$41.6K

$63K

$112.7K

How much do statistical modeling jobs pay per year?

As of Aug 14, 2026, the average yearly pay for statistical modeling in Seattle, WA is $63,025.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,800.00 and $68,300.00 per year, depending on experience, location, and employer.

What do statistical modeling do?

Statistical modeling involves creating mathematical representations of data to analyze patterns, make predictions, and inform decision-making. Professionals in this field use tools like statistical software and techniques such as regression analysis to interpret complex data sets. It is essential in fields like data science, research, and analytics to support evidence-based conclusions.

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 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 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 are popular job titles related to Statistical Modeling jobs in Seattle, WA?

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

What job categories do people searching Statistical Modeling jobs in Seattle, WA look for?

The top searched job categories for Statistical Modeling jobs in Seattle, WA are:

Statistical Modeling jobs near you
Infographic showing various Statistical Modeling job openings in Seattle, WA as of August 2026, with employment types broken down into 85% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $63,025 per year, or $30.3 per hour.

Quantitative Analyst - COMPASS Modeling

Think Tank, Inc.

Seattle, WA • On-site

Other

Re-posted 5 days ago

Job description

*Position is Subject to Contract Award POSITION DESCRIPTION:Description of Duties:Develop and advance the Comprehensive Passage (COMPASS) model for application in river systems to evaluate effects of stressors and management actions across fish life cycles, using statistical modeling, comp...

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