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Remote Anomaly Detection Jobs (NOW HIRING)

Hitachi

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR · On-site +1

$121K - $167K/yr

Hybrid (+50% Remote) - Remote 60% / Onsite 40% EXPECTED PAY RANGE: Data Scientist I: $99,608 - $136 ... Develop, train, and deploy ML models for Time-series forecasting and anomaly detection.

GDIT

FinOps Lead

WV · Remote

$161K - $218K/yr

... anomaly detection, forecasting, and compliance across the VA Enterprise Cloud Brokerage Service ... This position is primarily remote, however, the employee MUST live within 60 miles from either the ...

Maximus

Lead Operations Architect

VA · On-site +1

$55.50 - $76/hr

... anomaly detection #LI-Remote #clearance #techjobs #veteranspage Minimum Requirements TCS215, T5, Band 8 #TSTECH EEO Statement Maximus is an equal opportunity employer. We evaluate qualified ...

Mercor

Computer Vision MLE - Senior

New York, NY · Remote

$135/hr

Remote Duration: 3-4 weeks Commitment: 20+ hours/week Role Responsibilities * Benchmark baseline ... Experience with authentication, counterfeit, or anomaly detection. * Exposure to private equity ...

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Remote Anomaly Detection information

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How much do remote anomaly detection jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for remote anomaly detection in the United States is $27.67, according to ZipRecruiter salary data. Most workers in this role earn between $21.63 and $33.17 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Anomaly Detection Specialist, and why are they important?

To thrive in Remote Anomaly Detection, you need a strong background in statistics, data analysis, and machine learning, usually supported by a degree in computer science, engineering, or a related field. Familiarity with analytical tools like Python, R, SQL, and specialized anomaly detection frameworks is essential, along with experience in cloud platforms. Strong problem-solving skills, attention to detail, and effective remote communication set top performers apart. These competencies enable accurate identification of unusual patterns, quick response to potential risks, and seamless collaboration in distributed work environments.

What are some common challenges faced by professionals working in remote anomaly detection roles?

Professionals in remote anomaly detection often face challenges related to data quality and access, as much of the work depends on analyzing large, diverse datasets from various sources. Ensuring secure, real-time data transmission and maintaining robust communication with cross-functional teams can also be demanding, especially when working remotely. Additionally, adapting to evolving algorithms and staying current with the latest detection technologies requires ongoing learning and collaboration. Successfully navigating these challenges typically involves proactive communication, diligent documentation, and leveraging collaborative tools to stay connected with colleagues.

What is remote anomaly detection?

Remote anomaly detection is the process of identifying unusual patterns or behaviors in data collected from remote systems, devices, or networks. This technique is commonly used in industries such as cybersecurity, manufacturing, and IoT to monitor operations and quickly detect issues or potential threats. By using algorithms and machine learning, remote anomaly detection can automatically flag data points that deviate from normal patterns, helping organizations respond proactively to prevent problems. This approach is especially valuable in environments where manual monitoring is difficult or impractical due to distance or scale.

What is the difference between Remote Anomaly Detection vs Data Analyst?

AspectRemote Anomaly DetectionData Analyst
Required CredentialsBackground in cybersecurity, data science, or related fields; certifications like CompTIA Security+ or Certified Data ProfessionalBachelor's degree in statistics, mathematics, or related field; certifications like Microsoft Data Analyst Associate
Work EnvironmentRemote, often in tech or cybersecurity firms, focusing on monitoring systems and identifying irregularitiesRemote or on-site, working with data sets, creating reports, and providing insights for business decisions
Employer & Industry UsageTech companies, cybersecurity firms, financial institutionsBusiness, finance, marketing, healthcare sectors

While both roles involve working with data, Remote Anomaly Detection specialists focus on identifying irregularities in systems or networks, often requiring cybersecurity knowledge. Data Analysts interpret data to inform business strategies. The roles share skills in data analysis but differ in focus and industry applications.

More about Remote Anomaly Detection jobs
What cities are hiring for Remote Anomaly Detection jobs? Cities with the most Remote Anomaly Detection job openings:
What are the most commonly searched types of Anomaly Detection jobs? The most popular types of Anomaly Detection jobs are:
What states have the most Remote Anomaly Detection jobs? States with the most job openings for Remote Anomaly Detection jobs include:
What job categories do people searching Remote Anomaly Detection jobs look for? The top searched job categories for Remote Anomaly Detection jobs are:
Remote Anomaly Detection jobs near you
Infographic showing various Remote Anomaly Detection job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $57,562 per year, or $27.7 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 16 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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