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Data Analytics Manager Jobs in Reston, VA (NOW HIRING)

Parsons

Data Analytics Architect

Alexandria, VA · On-site +1

The Data Analytics Architect leads the design, integration, and governance of data systems that ... Establish data governance policies, data quality standards, and lifecycle management processes.

Highspring

Senior Manager, Data & Analytics

Mclean, VA · On-site

... Data Analytics practice. * Deliver on projects in the areas of data management, data governance, dashboard monitoring, DQ dashboards, data controls, data lineage, and data mapping. * Support data ...

Highspring

Senior Manager, Data & Analytics

Mclean, VA · On-site

... Data Analytics practice. * Deliver on projects in the areas of data management, data governance, dashboard monitoring, DQ dashboards, data controls, data lineage, and data mapping. * Support data ...

Airbus

Data Analytics Specialist

Dulles, VA · On-site

In this context we are looking for a Data Analytics Specialist to join our Digital & Analytics Team in Herndon, VA . WHAT'S IN IT FOR YOU Here is a selection of some of the benefits we offer our ...

Ag

Data Analytics Specialist

Dulles, VA · On-site +1

In this context we are looking for a Data Analytics Specialist to join our Digital & Analytics Team in Herndon, VA . WHAT'S IN IT FOR YOU Here is a selection of some of the benefits we offer our ...

Taoti

Marketing & Analytics Manager

Washington, DC · On-site

But marketing based on data and that evolves as result of what the ongoing analytics tell us is ... Manage and optimize Google Analytics 4 (GA4) implementations, conversion tracking, event ...

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All JobsData Analytics JobsData Analytics Manager JobsData Analytics Manager Jobs in Reston, VA

Data Analytics Manager information

See Reston, VA salary details

$32.3K

$101.3K

$179.3K

How much do data analytics manager jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data analytics manager in Reston, VA is $101,251.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,800.00 and $130,800.00 per year, depending on experience, location, and employer.

Will AI replace a data analyst?

AI tools can automate routine data processing and basic analysis tasks, but the role of a data analyst involves interpreting complex data, providing insights, and communicating findings, which require human judgment and domain expertise. Therefore, while AI may augment certain responsibilities, it is unlikely to fully replace data analysts in the near future, and skills in data storytelling and critical thinking remain essential.

How do Data Analytics Managers typically collaborate with stakeholders from non-technical departments?

Data Analytics Managers often act as a bridge between technical data teams and non-technical stakeholders, such as marketing, finance, or operations. They translate complex data insights into actionable recommendations and ensure that analyses align with business objectives. Regular communication, tailored presentations, and workshops are common practices to ensure all stakeholders understand the value and limitations of analytical findings. This collaborative approach helps drive data-driven decision-making across the organization.

What does a data analyst manager do?

A data analyst manager oversees a team of data analysts, guiding data collection, analysis, and reporting to support business decision-making. They develop strategies, ensure data accuracy, and often use tools like SQL, Excel, or data visualization software to interpret complex data sets. Strong leadership, communication skills, and knowledge of analytics tools are essential for this role.

How much do data analytics managers make?

Data analytics managers in the US typically earn a median salary of around $100,000 to $130,000 annually, with experienced professionals and those in high-demand industries earning higher. Salaries can vary based on location, education, certifications, and company size, and many roles require proficiency in tools like SQL, Python, or Tableau.

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

To thrive as a Data Analytics Manager, you need strong analytical skills, expertise in statistical methods, and a background in data science or a related field, often supported by a bachelor's or master's degree. Proficiency with data visualization tools (such as Tableau or Power BI), SQL, and analytics platforms like Python or R is typically required, along with experience in managing data projects. Leadership, strategic thinking, and effective communication are important soft skills for leading teams and translating data insights into actionable business strategies. These skills ensure that analytical initiatives drive business value and support informed decision-making across the organization.

What does a Data Analytics Manager do?

A Data Analytics Manager oversees data analysis operations and leads a team of analysts to extract actionable insights from data. They are responsible for managing data-driven projects, ensuring data integrity, and presenting findings to help guide business decisions. Their role often involves collaborating with various departments, setting analytic strategies, and ensuring that the team uses the most effective tools and methodologies. Additionally, they may handle hiring, training, and performance reviews of analytics staff.

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

AspectData Analytics ManagerData Analyst
ResponsibilitiesOversees analytics projects, manages teams, develops strategiesPerforms data collection, cleaning, and analysis to generate reports
Required SkillsLeadership, project management, advanced analyticsData manipulation, statistical analysis, visualization
QualificationsBachelor's or Master's in Data Science, Analytics, or related fields; certifications like CAP or Microsoft Certified Data AnalystBachelor's in Statistics, Mathematics, or related fields; certifications like Microsoft Certified Data Analyst
Work EnvironmentCorporate offices, analytics teams, cross-department collaborationData teams, business units, often in office or remote settings

In summary, a Data Analytics Manager leads analytics teams and strategies, requiring leadership skills and advanced certifications, while a Data Analyst focuses on data processing and reporting, with more technical and analytical tasks. Both roles are essential in data-driven organizations and often work closely together.

Is a data analyst a high salary?

Data analysts typically earn moderate to high salaries depending on experience, industry, and location. While entry-level positions may have lower pay, experienced data analysts with skills in SQL, Excel, and data visualization tools can command higher salaries, especially in competitive markets.
What are the most commonly searched types of Data Analytics jobs in Reston, VA? The most popular types of Data Analytics jobs in Reston, VA are:
What are popular job titles related to Data Analytics Manager jobs in Reston, VA? For Data Analytics Manager jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Data Analytics Manager jobs in Reston, VA look for? The top searched job categories for Data Analytics Manager jobs in Reston, VA are:
What cities near Reston, VA are hiring for Data Analytics Manager jobs? Cities near Reston, VA with the most Data Analytics Manager job openings:
Data Analytics Manager jobs near you
Infographic showing various Data Analytics Manager job openings in Reston, VA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 77% In-person, 8% Hybrid, and 15% Remote job distribution, with an average salary of $101,251 per year, or $48.7 per hour.
Technical Analytics Manager / Lead Data Scientist (Fraud Analytics & Investigative Support)

Technical Analytics Manager / Lead Data Scientist (Fraud Analytics & Investigative Support)

Praescient Analytics

Fairfax, VA • On-site, Remote

Full-time

Retirement, PTO

Posted 17 days ago

Job description

Location: Remote (Occasional Travel May Be Required)
Clearance: Ability to obtain and maintain a Public Trust
Position Overview
Praescient Analytics is seeking a highly skilled Technical Analytics Manager / Lead Data Scientist to provide technical leadership for a federal fraud analytics and investigative support program. This individual will serve as the technical authority responsible for designing innovative analytic approaches, developing advanced fraud detection models, leading model validation and quality assurance activities, and ensuring the successful delivery of reliable, defensible, and repeatable analytic solutions supporting federal oversight organizations.
The ideal candidate is a hands-on technical leader who combines deep data science expertise with strong leadership skills. They will guide multidisciplinary technical teams through the full analytics lifecycle, from ideation and data exploration to model development, testing, deployment, and continuous improvement, while mentoring technical staff and collaborating closely with Government stakeholders, investigators, and program leadership.
Key Responsibilities
  • Lead the design, development, testing, validation, deployment, and continuous improvement of advanced fraud detection and investigative analytics solutions.
  • Develop innovative analytic approaches to identify fraud, waste, abuse, and mismanagement across large-scale federal benefit programs.
  • Design and implement analytic rules, machine learning models, artificial intelligence (AI) solutions, natural language processing (NLP), anomaly detection, entity resolution, graph analytics, link analysis, risk scoring, and other advanced analytic capabilities.
  • Lead technical teams responsible for model development, experimentation, quality assurance, documentation, and production deployment.
  • Perform hands-on development of analytic models using open-source programming languages, frameworks, and data science tools.
  • Conduct exploratory data analysis, feature engineering, data profiling, model evaluation, and performance optimization across complex datasets.
  • Establish and oversee rigorous quality control processes to ensure analytic outputs are accurate, reliable, repeatable, and fully documented prior to Government delivery.
  • Review technical work products, source code, analytic methodologies, and model outputs produced by contractor support teams.
  • Identify technical risks, recommend mitigation strategies, and ensure timely delivery of high-quality analytic products.
  • Collaborate with Project Managers, Data Engineers, Graph Data Scientists, Investigative Analysts, Forensic Accountants, and Government stakeholders throughout the project lifecycle.
  • Present analytic methodologies, technical findings, model performance, and recommendations to Government leadership, investigators, and oversight organizations.
  • Support Agile delivery through sprint planning, backlog refinement, technical demonstrations, and iterative model development.

Required Qualifications
  • Must have experience with Fraud Analysis
  • Five (5) or more years of hands-on experience developing analytic rules and models for fraud detection use cases using leading-edge analytic tools and best practices.
  • Five (5) or more years of experience designing analytic approaches, managing model development and testing efforts, and conducting thorough quality control.
  • Demonstrated experience ideating innovative analytic use cases to detect and prevent fraud, waste, abuse, and mismanagement.
  • Five (5) or more years of experience tracking project progress, identifying technical risks, and delivering high-quality analytic solutions on schedule.
  • Five (5) or more years of experience reviewing contractor-developed analytic models, code, methodologies, and work products prior to final delivery.
  • Five (5) or more years of hands-on experience developing analytic rules and models using open-source programming languages and frameworks.
  • Strong written, verbal, presentation, and technical communication skills.
  • Demonstrated ability to lead technical teams while remaining actively engaged in hands-on analytics development.

Preferred Qualifications
Preference will be given to candidates with demonstrated experience in one or more of the following areas:
  • Developing fraud detection, fraud prevention, and program integrity analytics supporting pandemic relief, emergency assistance, grants, loans, healthcare, unemployment insurance, disaster relief, financial assistance, or other high-volume federal benefit programs.
  • Designing, developing, validating, deploying, and maintaining advanced analytic models utilizing machine learning, artificial intelligence (AI), natural language processing (NLP), anomaly detection, entity resolution, graph analytics, link analysis, knowledge graphs, risk scoring, or robotic process automation (RPA).
  • Applying open-source programming languages and frameworks such as Python, SQL, Spark, Pandas, Scikit-learn, TensorFlow, PyTorch, or comparable data science technologies.
  • Developing analytics within cloud-native environments utilizing Azure Databricks, Microsoft SQL Server, Microsoft Fabric, Azure Data Lake, Power BI, Neo4j, Git repositories, Lakehouse architectures, or enterprise data catalogs.
  • Working with large-scale public, non-public, commercial, financial, and law enforcement datasets to identify organized fraud rings, synthetic identities, duplicate entities, eligibility issues, and emerging fraud schemes.
  • Conducting exploratory data analysis, data profiling, feature engineering, model validation, performance testing, and quality assurance throughout the analytics lifecycle.
  • Supporting Offices of Inspector General (OIGs), law enforcement organizations, oversight agencies, or program integrity initiatives through advanced analytic solutions.
  • Developing reproducible analytic workflows that emphasize governance, documentation, transparency, explainability, and enterprise data management best practices.
  • Leading technical reviews, mentoring data scientists, and establishing quality standards for analytic products delivered to Government customers.

What We're Looking For
We're looking for a technical leader who enjoys solving complex fraud detection challenges while remaining actively involved in hands-on analytics development. The ideal candidate is equally comfortable writing code, designing machine learning models, reviewing technical work products, mentoring fellow data scientists, and briefing analytic findings to senior Government stakeholders. They combine innovative thinking with disciplined engineering practices to ensure every analytic solution is technically sound, operationally effective, and capable of supporting real-world investigative and oversight missions.
What you can expect from us:
  • Real opportunity for career growth in an environment where your achievements will be celebrated
  • Constant collaboration with numerous teams to ensure client success
  • A team that respects and embraces your ideas and expertise
  • Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain
  • A workplace dedicated to supporting and bettering public safety and government agencies

Benefits:
  • Competitive salary based on qualifications and experience
  • Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
  • 401(k) with company match
  • Travel & performance incentives
  • 3 weeks paid time off (plus Federal Holidays)
  • $5K annual training allowance
  • $500 book allowance
  • Tuition reimbursement program

Praescient Analytics is an Equal Employment Opportunity employer. Employment decisions are based on merit, qualifications, experience, performance, business needs, and applicable contract requirements. Praescient does not unlawfully discriminate or provide disparate treatment based on race, ethnicity, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other status protected by applicable law.
Praescient Analytics acknowledges the applicable clause and provision updates implementing Executive Order 14398, Addressing DEI Discrimination by Federal Contractors, and the related FAR/RFO updates, including FAR 52.222-90 where applicable. Praescient does not engage in racially discriminatory DEI activities, including disparate treatment based on race or ethnicity in recruitment, hiring, promotion, contracting, program participation, training, mentoring, leadership development, or allocation of company resources. Praescient's employment and contracting decisions are made based on merit, qualifications, experience, performance, business needs, and applicable contract requirements.
Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information.
US Citizenship Required
Interested Candidates: Please forward your resume to recruiting@praescientanalytics.com and please visit our website to apply online at www.praescientanalytics.applicantstack.com/x/openings.

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