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Statistical Modeling Jobs in Seattle, WA (NOW HIRING)

Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect ...

In this role, you will engage in exploratory and descriptive analysis, statistical modeling, and creating data visualizations to help solve complex business problems and inform strategic decisions.

Support senior management by managing metrics reporting and performing mathematical and statistical modeling to produce business forecasts. Research, design, and develop new forecasting technologies ...

Sr. Applied Scientist, Prime AI/ML Science

Seattle, WA · On-site

$104K - $142K/yr

... and statistical modeling techniques. - Stay abreast of current literature in the field and advance/build novel science solutions leveraging SoTA solutions. - Build and develop AI/ML models and ...

Showing results 41-60

Statistical Modeling information

See Seattle, WA salary details

$41.5K

$63K

$112.7K

How much do statistical modeling jobs pay per year?

As of Sep 3, 2026, the average yearly pay for statistical modeling in Seattle, WA is $62,990.00, 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 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 Seattle, WA?

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

Infographic showing various Statistical Modeling job openings in Seattle, WA as of August 2026, with employment types broken down into 84% Full Time, 12% Part Time, and 4% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $62,990 per year, or $30.3 per hour.

Data Scientist, WW Ops FP&A

Amazon

Bellevue, WA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 hours ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,146 frontline employees who took The Breakroom Quiz

5th of 39 rated national retailers


Job description

The WW Operations IPAT team is revolutionizing Amazon's financial forecasting through TrendCast, an innovative, automated, science-based top-down forecast modeling engine. As we expand our scope into Generative AI, we are building a sophisticated, LLM-powered Finance Knowledge Base to streamline decision-making. We are seeking a strong Data Scientist II to drive the technical strategy for these advanced analytical and AI-driven solutions. In this role, you will act as a technical lead, translating high-level business ambiguity into scalable, production-grade systems while influencing cross-functional roadmaps.
Key job responsibilities
• Own and solve difficult business problems where the solution approach is unclear, delivering high-quality artifacts that directly influence financial decisions for senior leadership
• Apply a range of data science methodologies (statistical modeling, machine learning, time series analysis, econometrics) to solve complex forecasting challenges
• Design and implement scalable, reliable approaches to extract insights from large, complex datasets across multiple domains
• Develop metrics to quantify the benefits of solutions and measure project progress and success
• Design and implement Retrieval-Augmented Generation (RAG) systems and LLM-based solutions to enhance financial knowledge retrieval and decision support
• Proactively identify and solve challenges related to GenAI solutions including accuracy, latency, and context management
• Partner with finance stakeholders, engineers, and other scientists to identify data requirements and deliver solutions that meet customer needs
• Write clear, factually correct documents with substantial analytical components; explain technical concepts to non-technical audiences
• Provide peer feedback on solutions and results; mentor and teach less experienced data scientists
BASIC QUALIFICATIONS
- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ years of guiding and coaching a group of researchers experience
- 1+ years of working with or evaluating AI systems experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience applying theoretical models in an applied environment
PREFERRED QUALIFICATIONS
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience working on multi-team, cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually

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About Amazon

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Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US