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Predictive Modeling Jobs in Virginia (NOW HIRING)

Develop probabilistic and/or predictive models to support analytic objectives. * Implement machine learning processes into production software applications. * Use big data tools and proprietary data ...

Develop probabilistic and/or predictive models to support analytic objectives. * Implement machine learning processes into production software applications. * Use big data tools and proprietary data ...

Develop probabilistic and/or predictive models to support analytic objectives. * Implement machine learning processes into production software applications. * Use big data tools and proprietary data ...

Support advanced analytics capabilities, including statistical analysis, predictive modeling, trend analysis, root cause analysis, and AI-enabled analytics. * Ensure data sharing, API integration ...

Health IT Data Scientist

Alexandria, VA · On-site +1

$110K - $120K/yr

Develop predictive models and machine learning algorithms. * Perform statistical analyses on structured and unstructured data. * Identify trends, patterns, and performance indicators. * Develop ...

... predictive models to support analytic objectives. • Implement machine learning processes into production software applications. • Use big data tools and proprietary data to answer mission and ...

Showing results 21-40

Predictive Modeling information

See Virginia salary details

$10

$58

$82

How much do predictive modeling jobs pay per hour?

As of Jul 25, 2026, the average hourly pay for predictive modeling in Virginia is $58.21, according to ZipRecruiter salary data. Most workers in this role earn between $52.21 and $67.69 per hour, depending on experience, location, and employer.

What is the highest paying modeling job?

In predictive modeling, senior data scientists and machine learning engineers typically earn the highest salaries, often exceeding six figures annually. These roles require advanced skills in statistical analysis, programming, and experience with tools like Python or R, and they are often found in industries such as finance, technology, and healthcare.

What are the key skills and qualifications needed to thrive in the Predictive Modeling position, and why are they important?

To thrive in Predictive Modeling, you need strong statistical analysis, data mining, and machine learning skills, often supported by a degree in statistics, computer science, mathematics, or a related field. Expertise with tools such as Python, R, SAS, or SQL, as well as knowledge of data visualization software, is commonly required, and certifications in data science or analytics are a plus. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills for this role. Mastering these skills enables professionals to build accurate models, interpret data-driven results, and clearly communicate insights to stakeholders, which are critical for informed business decision-making.

What is a Predictive Modeling job?

A Predictive Modeling job involves using statistical techniques, machine learning algorithms, and data analysis to forecast future outcomes based on historical data. Professionals in this role build and test models to identify patterns, trends, and relationships in complex datasets. They commonly work in industries like finance, healthcare, and marketing to improve decision-making and optimize business processes. Strong skills in programming, data manipulation, and statistical analysis are essential for success in this role.

What is a predictive modeler?

A predictive modeler is a professional who develops statistical and machine learning models to forecast future outcomes based on historical data. They use tools like Python, R, or SAS and often require strong analytical skills and knowledge of data science techniques. Their work supports decision-making in various industries such as finance, marketing, and healthcare.

Is 40 too late for data science?

Predictive modeling is a key role in data science, and age is not a barrier to entering the field. Many professionals transition into data science later in their careers by developing skills in programming, statistics, and tools like Python or R, often through online courses or certifications. Success depends on your ability to learn and apply relevant skills, regardless of age.

What does a typical workday look like for someone working in predictive modeling?

A typical day in predictive modeling involves gathering and cleaning data, selecting relevant features, and building statistical or machine learning models to forecast trends or behaviors. You’ll regularly use programming languages and analytics tools to test model performance and iterate on results, while documenting findings and preparing reports for internal teams or clients. Collaboration is often required with data engineers, subject matter experts, and business leaders to ensure that models align with organizational goals. Additionally, you may be tasked with presenting your insights to both technical and non-technical audiences, making strong communication skills essential for success in this role.

What jobs will no longer exist in 2030?

Predictive modeling roles may decline as automation and AI tools increasingly handle data analysis and forecasting tasks. Jobs that involve routine, repetitive tasks are also at risk of automation, potentially reducing demand for certain administrative or manual roles. However, new jobs may emerge in AI oversight, data ethics, and advanced analytics.
What are the most commonly searched types of Predictive Modeling jobs in Virginia? The most popular types of Predictive Modeling jobs in Virginia are:
What job categories do people searching Predictive Modeling jobs in Virginia look for? The top searched job categories for Predictive Modeling jobs in Virginia are:
Infographic showing various Predictive Modeling job openings in Virginia as of July 2026, with employment types broken down into 68% Full Time, 12% Part Time, 2% Temporary, and 18% Contract. Highlights an 67% Physical, 3% Hybrid, and 30% Remote job distribution, with an average salary of $121,075 per year, or $58.2 per hour.
Data Science Manager, PXT Central Science

Data Science Manager, PXT Central Science

Amazon

Arlington, VA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 11 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,010 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Every day, hundreds of thousands of Amazon associates show up to fulfill the promise we make to our customers. Behind the workforce decisions that support them - staffing, retention, scheduling, development - there should be science that doesn't just describe what happened, but explains why it happened and predicts what comes next. That's the work we do.
PXT Central Science (PXTCS) is Amazon's internal research organization dedicated to bringing scientific rigor to people and workforce decisions at global scale. Our team sits within the part of PXTCS that focuses on Amazon's Tier 1 hourly populations - the associates at the heart of Amazon's operations. We are a multidisciplinary group of 15 economists, data scientists, data engineers, and research scientists united by a single mission: to transform complex operational challenges into actionable insights through rigorous causal analysis and predictive modeling that empowers data-driven workforce decisions.
We are building something new - causal predictive models that go beyond traditional forecasting. Our models don't just tell leaders what will happen; they reveal why it will happen and what levers they can pull to change the outcome. This is the frontier where causal inference meets modern machine learning, and we need a scientist who can help us push it forward.
As a Data Science Manager (DSM), you will lead a team of economists, scientists, and data engineers working to solve complex scientific problems that have high business and customer impact. You will be responsible for building structural and predictive models, leveraging data science workflows, and driving innovations that deliver measurable results for Amazon customers.
You will work shoulder-to-shoulder with economists who deeply understand the causal mechanisms driving workforce dynamics and data scientists who know the operational landscape - and you will bring the technical creativity to expand what's possible. That means writing production-quality code that our partner engineering teams can implement into decision-making tools. It means exploring novel feature spaces - large language models, computer vision, and other emerging techniques - to unlock signal that traditional approaches miss. And it means doing all of this with the scientific rigor that causal claims demand.
This role is built for someone who is entrepreneurial and energized by ambiguity - someone who sees a prototype model and immediately starts thinking about how to make it robust, scalable, and impactful. You will not just advance your own work; you will elevate the scientists around you.
If you want to do science that directly shapes how Amazon supports its workforce - not in theory, but in production systems that leaders use to make better decisions every day - we'd love to talk.
Key job responsibilities
- Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
- Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
- Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
- Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions
About the team
The Central Science Team within Amazon's People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and UX to develop and deliver solutions that measurably achieve this goal.
BASIC QUALIFICATIONS
- 5+ years of building quantitative solutions as a scientist or science manager experience
- 2+ years of scientists or machine learning engineers management experience
- 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Knowledge of Python or R or other scripting language
PREFERRED QUALIFICATIONS
- Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
- Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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, CA, San Francisco - 201,300.00 - 272,400.00 USD annually
USA, MA, Boston - 175,100.00 - 236,900.00 USD annually
USA, VA, Arlington - 175,100.00 - 236,900.00 USD annually
USA, WA, Bellevue - 175,100.00 - 236,900.00 USD annually
USA, WA, Seattle - 175,100.00 - 236,900.00 USD annually

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About Amazon

Sourced by ZipRecruiter

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 and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US