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Predictive Analytics Jobs in Virginia (NOW HIRING)

Senior Data Scientist

Alexandria, VA · On-site

$180 - $260/hr

Apply cutting‑edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics * Work with diverse data types (structured ...

... and predictive analytics. * Strong leadership, mentoring, and teamguidance abilities. * Excellent communication and presentation skills, including the ability to translate complex analytics for ...

Showing results 41-60

Predictive Analytics information

See Virginia salary details

$26.8K

$111.8K

$198.8K

How much do predictive analytics jobs pay per year?

As of Aug 15, 2026, the average yearly pay for predictive analytics in Virginia is $111,755.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,800.00 and $121,900.00 per year, depending on experience, location, and employer.

What is predictive analytics?

A Predictive Analytics job involves using statistical techniques, machine learning models, and data analysis to forecast future trends and outcomes. Professionals in this field work with large datasets to identify patterns, assess risks, and provide data-driven recommendations. They commonly apply predictive models in industries such as finance, marketing, healthcare, and supply chain management. The role typically requires expertise in programming languages like Python or R, data visualization, and strong problem-solving skills.

What is a predictive analytics job description?

A predictive analytics job involves analyzing data to develop models that forecast future trends and behaviors. Professionals in this role use statistical techniques, machine learning tools, and programming languages like Python or R to interpret data and support decision-making. Strong analytical skills and knowledge of data management are essential for success in this field.

What are some typical challenges faced in a predictive analytics position?

Professionals in Predictive Analytics often encounter challenges such as dealing with incomplete or inconsistent data, selecting the most appropriate modeling techniques, and ensuring models are both accurate and interpretable for business stakeholders. Additionally, balancing multiple projects with tight deadlines and aligning analytics solutions with strategic objectives can be demanding. However, these challenges provide excellent opportunities for creative problem-solving, collaboration with various departments, and continuous learning in a rapidly evolving field. Supportive team structures and access to up-to-date analytical tools typically help professionals overcome these obstacles. Embracing these challenges can significantly enhance your expertise and career trajectory in predictive analytics.

What do predictive analytics do?

Predictive analytics involves analyzing historical data to identify patterns and forecast future outcomes. In a predictive analytics role, professionals use statistical models, machine learning algorithms, and data visualization tools to support decision-making and improve business strategies.

What jobs use predictive analytics?

Predictive analytics is used in a variety of roles such as data analyst, data scientist, business analyst, and risk analyst. These jobs involve analyzing data to forecast trends, improve decision-making, and optimize processes, often requiring skills in statistical modeling, machine learning, and tools like Python or R.

What are the key skills and qualifications needed to thrive in predictive analytics?

To thrive in Predictive Analytics, you need strong skills in statistical analysis, data modeling, and a solid educational background in mathematics, statistics, computer science, or a related field. Proficiency with tools such as Python, R, SQL, and data visualization platforms, as well as certifications like SAS or Microsoft Certified Data Analyst, is highly valued. Excellent problem-solving abilities, attention to detail, and effective communication are crucial soft skills for translating complex data into actionable insights. These skills are essential for accurately forecasting trends, informing business decisions, and effectively collaborating with cross-functional teams.

What are the most commonly searched types of Predictive Analytics jobs in Virginia?

The most popular types of Predictive Analytics jobs in Virginia are:

Infographic showing various Predictive Analytics job openings in Virginia as of August 2026, with employment types broken down into 1% Internship, 92% Full Time, 4% Part Time, and 3% Contract. Highlights an 78% Physical, 7% Hybrid, and 15% Remote job distribution, with an average salary of $111,755 per year, or $53.7 per hour.

Senior Data Scientist (OBI Advanced Analytic Method Augmentation) - OBIQUA

CELESTAR

Reston, VA • On-site

Full-time

Medical, Dental, Life, Retirement, PTO

Re-posted 8 days ago


Job description

Celestar Corporation is seeking a Senior Data Scientist (OBI Advanced Analytic Method Augmentation) to support The Defense Intelligence Agency (DIA) under the Object Based Intelligence and Quality Assurance (OBIQUA) task order. The primary place of performance will be at DIA Facilities across the National Capital Region (NCR). If interested and meet the qualifications, we encourage you to apply for this rewarding and impactful opportunity.
ANTICIPATED AWARD: TBD
ANTICIPATED START: TBD
PERIOD OF PERFORMANCE: 1 Base Year + 4 Option Years
LOCATION: DIA Facilities across the National Capital Region (NCR)
CLEARANCE REQUIREMENT: Active TS/SCI with a Current CI Poly
About Us:
Celestar, a proud Veteran-Owned company, offers highly competitive salaries and benefits. Our comprehensive benefits package includes company-paid employee and family dental insurance, employee health insurance, life insurance, and disability coverage. Additionally, we provide a 401(k)-retirement plan with company matching, paid holidays, and personal time off.
Responsibilities:
This opportunity will support multiple DIA initiatives, including the Machine-Assisted Rapid-Repository System (MARS), Object Management Services (OMS), and Object-Based Intelligence (OBI).
• The Senior Data Scientist (OBI Advanced Analytic Method Augmentation), Conducts data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions.
• Proactively retrieves information from various sources, analyzes it for better understanding about the data set, and builds AI tools that automate certain processes.
• Duties typically include: creating various ML-based tools or processes, such as recommendation engines or automated lead scoring systems.
• Performs statistical analysis, applies data mining techniques, and builds high quality prediction systems.
• Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as Rand Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
• Should have prior experience with large data multi-INT analytics, ML, and automated predictive analytics.
• Designs, develops, and evaluates leading-edge algorithmic intelligence concepts, practices, and technologies for implementation into all-source analysis tradecraft, assessments, production, and dissemination.
• Proposes advanced statistical or mathematical techniques and methodology that may permit identification and evaluation of alternatives, assists in model formulation or experimental test design, and shares jointly in team responsibility for development of advanced analytic techniques and assessments.
• Evaluates data science, artificial intelligence, and other advanced analytic methods for risks, biases, and limitations that would distort conclusions.
• Conducts continuous independent research on methods of analysis in government, industry, and academia to keep abreast of the state of the art, keeps senior leadership apprised of the advances and applicability to programs.
• Utilizes in-depth knowledge of relevant theories, techniques, procedures and processes to investigate, prototype, and evaluate technologies to improve all-source intelligence analysis.
• Provides technical input into and participates in the development of software and computer graphics systems.
• Performs research studies to understand the process of augmenting or automating all source analytic processes using various computer models.
• Provides incremental enhancements to tools, capabilities, processes, and methods.
• Possesses in-depth knowledge and experience in using data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions.
• Writes either R or Python scripts to drive data science workflows, have experience using SQL, and managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
• Possesses prior experience with large data, spatial data, multi-INT analytics, ML, and automated predictive analytics.
• Works with ambiguous information, deconstruct key questions, leverage spatial data, exploit application programming interfaces, suggest methodologies, develop data schemas to structure observations. This requires working knowledge of coding and scripting, information science, mathematics, machine learning, visual analytic modeling tools, and relevant Standard Operating Procedures (SOPs) to create repeatable, widely applicable procedures to support all-source intelligence analysis and production.
• Creates and works in distributed analytic environments, scaling algorithms to work on increasingly large and complex datasets that are larger than RAM.
• Serves as the primary POC for data science expertise, ensuring tradecraft compliance and analytic standards as it relates to data science techniques on the contract.
• Provides advice on emerging data science methods, tools, algorithms, training, or requirements to advance DIA's analytic edge in its use of data science.
• Works with DIA vendors and the software developers to implement distributed algorithms to work on increasingly large and complex data sets.
• Review and evaluate OBI documentation submitted by advanced analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in AI system development and deployment.
• Assess OBI documentation for completeness, accuracy, and thoroughness, and provide detailed feedback to owners and developers.
• Provide consultation and guidance to data and AA owners, developers, and stakeholders on OBI governance and knowledge modeling, including best practices for system development, testing, and deployment.
• Assist analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language.
• Collaborate with stakeholders to develop, implement, and refine best practices for translating technical documentation into tradecraft compliant language
• Review and edit translated documentation to ensure accuracy, completeness, and adherence to tradecraft standards.
• Collaborate with the Computer Scientist to develop and implement testing methodologies for system validation and evaluation.
• Conduct audits to ensure compliant use of systems for approved use-cases in all source analysis.
• Develop and maintain a repository of audit findings and recommendations to facilitate knowledge sharing and best practices across the organization.
• Design and execute TEVV protocols to evaluate the performance, robustness, and fairness of systems in all source analysis contexts.
• Develop and apply statistical models and methods to analyze TEVV results and identify areas for improvement.
• Collaborate with stakeholders to develop and implement corrective actions to address TEVV findings.
• Develop and track performance metrics to evaluate the effectiveness of systems in all source analysis.
• Analyze and interpret performance metrics to identify trends, patterns, and areas for improvement.
• Collaborate with stakeholders to develop and implement data-driven decision-making processes to inform system development and improvement.
• Develop and refine methodologies for evaluating system performance, robustness, and fairness in all source analysis contexts.
• Collaborate with stakeholders to develop and implement best practices for system development, testing, and deployment.
• Supports capability development by contributing, editing, and storing code in Government owned/controlled source version control repositories.
Required qualifications/skills:
• Minimum 12 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a master's degree.
-OR-
• A minimum of 17 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a bachelor's degree.
• Must have at least 8 years of experience in AI implementation, advanced degree in computer science, data science, or related field.
• Must have expertise in AI algorithms, model development, TEVV, and operationalization.
• Possesses a professional or graduate certificate in data science from a university, major online learning platform (all business for Data Scientists at any experience level).
• Demonstrates ability to work independently and with minimal oversight.
• Active TS/SCI Clearance within the past 5 years.
Come on board with a company that Values its Employees!
Celestar Corporation is an Equal Opportunity Employer. The Celestar Corporation prohibits discrimination, harassment, and retaliation in employment based on race; color; religion; genetic information; national origin; sex (including same-sex); sexual orientation; gender identity; pregnancy, childbirth, or related medical conditions; age; disability or handicap; citizenship status; marital status; service member/protected veteran status; or any other category protected by federal, state, or local law.