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Data Science Analytics Jobs in Washington (NOW HIRING)

Elder Research

Data Scientist

Arlington, VA · On-site

Explore, clean, and wrangle large, complex datasets to uncover insights and identify opportunities for data science-driven solutions in support of assessments, gap analyses, and actionable ...

Elder Research

Data Scientist

Arlington, VA

Explore, clean, and wrangle large, complex datasets to uncover insights and identify opportunities for data science-driven solutions in support of assessments, gap analyses, and actionable ...

Guidehouse

Senior Data Scientist

Chantilly, VA

Data Science Consulting Travel Required: None Clearance Required: Active Top Secret SCI with Polygraph What You Will Do: Our Data and Analytics consultants help clients maximize the value of their ...

Guidehouse

Senior Data Scientist

Chantilly, VA · On-site

Data Science Consulting Travel Required: None Clearance Required: Active Top Secret SCI with Polygraph What You Will Do: Our Data and Analytics consultants help clients maximize the value of their ...

Guidehouse

Senior Data Scientist

Chantilly, VA

Data Science Consulting Travel Required: None Clearance Required: Active Top Secret SCI with Polygraph What You Will Do: Our Data and Analytics consultants help clients maximize the value of their ...

Elder Research

Data Scientist

Arlington, VA

Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences * 2-10+ years of experience in data ...

Vantor

Data Scientist

Reston, VA · On-site

Required : • Current/active TS/SCI security clearance and be willing and able to obtain CI polygraph. • 5 years of professional experience in data science, analytics, or data engineering roles ...

Peraton

Data Scientist

Washington, DC · On-site

$112K - $179K/yr

Build and integrate data science solutions within the ServiceNow platform, including Performance Analytics, custom applications, and workflow automation * Analyze large, complex datasets to identify ...

Vantor

Data Scientist

Reston, VA · On-site

Required : • Current/active TS/SCI security clearance and be willing and able to obtain CI polygraph. • 5 years of professional experience in data science, analytics, or data engineering roles ...

Peraton

Data Scientist

Washington, DC

$112K - $179K/yr

Build and integrate data science solutions within the ServiceNow platform, including Performance Analytics, custom applications, and workflow automation * Analyze large, complex datasets to identify ...

Peraton

Data Scientist

Washington, DC · On-site

$112K - $179K/yr

Build and integrate data science solutions within the ServiceNow platform, including Performance Analytics, custom applications, and workflow automation * Analyze large, complex datasets to identify ...

Leidos

Data Scientist

Washington, DC · On-site

$69K - $125K/yr

You will be part of a research-focused data science team working to advance national security objectives, produce and analyze results, disseminate findings, and contribute to publications and ...

Leidos

Data Scientist

Bethesda, MD

You will be part of a research-focused data science team working to advance national security objectives, produce and analyze results, disseminate findings, and contribute to publications and ...

Leidos

Data Scientist

Bethesda, MD · On-site

$69K - $125K/yr

You will be part of a research-focused data science team working to advance national security objectives, produce and analyze results, disseminate findings, and contribute to publications and ...

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Data Science Analytics information

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How much do data science analytics jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for data science analytics in Washington is $62.01, according to ZipRecruiter salary data. Most workers in this role earn between $49.81 and $70.24 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Analytics professional, and why are they important?

To thrive in Data Science Analytics, a strong background in statistics, data modeling, and programming (often with a degree in computer science, mathematics, or a related field) is essential. Familiarity with tools such as Python, R, SQL, and data visualization platforms like Tableau or Power BI, as well as knowledge of machine learning libraries, is typically required. Critical thinking, problem-solving, and effective communication skills help professionals translate complex data insights into actionable business strategies. These competencies are crucial for extracting meaningful information from data and driving informed decision-making within organizations.

How do data science analytics professionals typically collaborate with other departments within an organization?

Data science analytics professionals often work closely with teams across the organization, such as marketing, finance, product development, and IT. Their role involves understanding business needs, gathering requirements, and translating complex data findings into actionable insights for non-technical stakeholders. Effective communication and teamwork are essential, as data scientists may participate in cross-functional meetings, present their analyses, and tailor their recommendations to support strategic decision-making. This collaborative approach not only enhances the impact of analytics projects but also fosters continuous learning and innovation within the organization.

What is the difference between Data Science Analytics vs Data Analyst?

AspectData Science AnalyticsData Analyst
Required CredentialsDegree in Data Science, Statistics, or related fields; programming skillsDegree in Statistics, Mathematics, or related fields; proficiency in Excel and SQL
Work EnvironmentOften involves complex modeling, machine learning, and predictive analyticsFocuses on data cleaning, reporting, and visualization
Employer & Industry UsageTech companies, finance, healthcare, and research institutionsBusiness, marketing, finance, and operations across various industries

Data Science Analytics and Data Analysts both work with data, but Data Science Analytics typically involves advanced modeling and predictive techniques, while Data Analysts focus on data reporting and visualization. The roles often overlap, but Data Science Analytics requires more technical skills and a deeper understanding of algorithms.

What is data science analytics?

Data science analytics is the process of extracting insights and knowledge from data using statistical, mathematical, and computational techniques. It involves collecting, cleaning, analyzing, and visualizing data to help organizations make informed decisions. Professionals in this field use tools like Python, R, and SQL to interpret complex data sets, build predictive models, and identify trends or patterns. Data science analytics plays a key role in industries such as finance, healthcare, retail, and technology, enabling businesses to optimize operations and improve outcomes.
What are the most commonly searched types of Data Science Analytics jobs in Washington? The most popular types of Data Science Analytics jobs in Washington are:
What are popular job titles related to Data Science Analytics jobs in Washington? For Data Science Analytics jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Data Science Analytics jobs in Washington look for? The top searched job categories for Data Science Analytics jobs in Washington are:
Data Science Analytics jobs near you
Data Scientist

Data Scientist

Elder Research

Arlington, VA • On-site

Full-time

Posted 29 days ago

Job description

Data Scientist
General Information
Requisition # 674
Locations USA-VA-Arlington
Posting Date 03/04/2026
Security Clearance Required - IRS MBI
Remote Type Hybrid
Time Type Full time
Description & Requirements
Elder Research Inc., a wholly owned subsidiary of MANTECH international Corporation seeks a motivated, career and customer-oriented Data Scientist to join our team in Arlington, VA. This role is a remote role preferably in the Washington DC area.
As a Data Scientist, you will support the Internal Revenue Service's mission to improve tax compliance, fraud detection, and risk identification across large, complex tax and financial data environments. You will work directly with government clients, program managers, and technical teams to understand business and compliance challenges, design analytical approaches, and deliver data-driven solutions that inform enforcement, audit prioritization, and fraud prevention efforts.
In this role, you will develop, test, and deploy predictive and statistical models using structured and unstructured data to identify anomalies, non-compliance risk, and potential fraud within tax records and related datasets. You will contribute across the full data science lifecycle, from problem formulation and data exploration through model validation, deployment, and stakeholder communication.
Responsibilities include but are not limited to:
  • Prior programming experience, preferably in Python or R, including data exploration, feature engineering, model development, and writing modular, reusable, well-documented code within an iterative development process that includes peer review and collaboration
  • Demonstrated experience using Python, SQL, and Databricks for data analysis, modeling, statistical evaluation, and working with Markdown for technical documentation
  • Explore, clean, and wrangle large, complex datasets to uncover insights and identify opportunities for data science-driven solutions in support of assessments, gap analyses, and actionable recommendations for IRS stakeholders
  • Design, develop, test, validate, and implement quantitative and qualitative data science solutions and predictive risk models (including audit selection, refund review, and fraud prevention initiatives) that are modular, maintainable, adaptable to evolving government and regulatory requirements, and supported by robustness, sensitivity, and significance testing to ensure defensible and explainable results
  • Apply statistical and machine learning techniques (supervised and unsupervised) to anomaly detection, fraud identification, and non-compliance risk scoring to help prioritize cases based on compliance risk, fraud indicators, and business impact
  • Collaborate with clients, subject matter experts, and cross-functional teams to refine problem statements, requirements, and analytical approaches, while demonstrating the ability to work independently in a collaborative, fast-paced environment
  • Prepare and deliver technical and non-technical briefings, reports, and presentations to audiences with varying levels of analytical sophistication, translating business and compliance needs into technical solutions with strong interpersonal, written, and verbal communication skills

Minimum Qualifications:
  • Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences
  • 2-10+ years of experience in data science, analytics, or a related technical field
  • Experience using version control systems (e.g., Git) and collaborative development practices
  • Strong understanding of relational databases and SQL
  • Comfortable learning new tools, methodologies, and domains, including working outside your comfort zone
  • Strong analytical mindset with a willingness to tackle complex mathematical and statistical challenges
  • Willingness to travel and work on-site at client locations as required by project needs

Preferred Qualifications:
  • Advanced degree (MS or PhD) in statistics, computer science, data science, mathematics, analytics, engineering, or related fields; experience applying advanced statistical concepts including sampling considerations, bias detection, weighting techniques, handling missing or outlier data, exploratory analysis, and longitudinal forecasting; and understanding of the data analytics lifecycle (e.g., CRISP-DM)
  • Experience with PySpark, Unity Catalog, and Jobs in Databricks, with familiarity using platforms and tools such as Databricks and AWS
  • Experience with Natural Language Processing (NLP) and text analytics applied to unstructured documents or case notes, as well as graph analytics and network analysis to identify relationships, fraud rings, or interconnected entities
  • Experience with containerization and environment management (e.g., venv, conda)
  • Experience operating in secure or remote government environments, including use of bash and command-line tools

Clearance Requirements:
  • Must currently possess an IRS Public Trust clearance with Full Background Investigation

Physical Requirements:
  • Must be able to remain in a stationary position 50%
  • Needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
  • Frequently communicates with co-workers, management, and customers, which may involve delivering presentations. Must be able to exchange accurate information in these situation

About Elder Research, Inc - People Centered. Data Driven
Elder Research considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation.
If you need a reasonable accommodation to apply for a position with Elder Research, please email us at careers@elderresearch.com and provide your name and contact information.

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