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Anomaly Detection Jobs (NOW HIRING)

Wise Skulls

AI/ML Data Scientist

Phoenix, AZ · On-site

This position plays a critical role in advancing our anomaly detection, root cause analysis, and intelligent automation capabilities across enterprise systems. * The ideal candidate will bring deep ...

DetaPent

Junior Data Scientist

Columbia, SC · On-site +1

$60K - $90K/yr

Develop, optimize, and maintain computational models for debit transaction anomaly detection using AI/ML techniques. Perform data analysis, generate insights, and identify patterns to support ...

True Anomaly

Machine Learning Engineer

Denver, CO · On-site

$85K - $180K/yr

Working alongside experienced engineers, you will support the development of models and pipelines that enable object classification, anomaly detection, and data-driven decision-making. You are ...

Appgate

Principal Machine Learning Engineer

Manhattan, NY · On-site

$220K - $265K/yr

Architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral analysis. * Develop and maintain end-to-end ML pipelines: data ingestion, feature engineering, model ...

Appgate

Staff Machine Learning Engineer

Manhattan, NY · On-site

$180K - $220K/yr

Architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral analysis. * Develop and maintain end-to-end ML pipelines: data ingestion, feature engineering, model ...

Microsoft

Senior Security Researcher

Redmond, WA · On-site

... anomaly detection. * OR Bachelor's Degree in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 4+ years experience in software development lifecycle, large-scale ...

Microsoft

Senior Security Researcher

Redmond, WA · On-site

... anomaly detection. * OR Bachelor's Degree in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 4+ years experience in software development lifecycle, large-scale ...

Advantest

Thermal Engineering R&D Intern

San Jose, CA · On-site

$19.75 - $25.50/hr

Research, develop, and test ML models (Regression, Time-Series, Anomaly Detection) using Python frameworks like TensorFlow, PyTorch, or Scikit-learn to improve thermal monitoring and prediction.

Microsoft

Principal Security Researcher

Redmond, WA · On-site

... anomaly detection. * OR Master's Degree in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 4+ years experience in software development lifecycle, large-scale ...

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How much do anomaly detection jobs pay per hour?

As of May 29, 2026, the average hourly pay for anomaly detection in the United States is $38.48, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $51.68 per hour, depending on experience, location, and employer.

What is an Anomaly Detection job?

An Anomaly Detection job involves identifying unusual patterns or deviations in data that do not conform to expected behavior. Professionals in this role use statistical methods, machine learning, and AI techniques to detect fraudulent activities, network intrusions, or system failures. They work in various industries such as finance, cybersecurity, healthcare, and manufacturing. Responsibilities may include data preprocessing, model training, and real-time anomaly detection to improve security and operational efficiency.

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

To thrive in an Anomaly Detection role, you need a strong background in data analysis, statistics, and machine learning, often supported by a degree in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, and experience using data analysis tools such as TensorFlow, Scikit-learn, or specialized anomaly detection frameworks, are typically required. Strong problem-solving skills, attention to detail, and effective communication enhance your ability to interpret findings and share insights with cross-functional teams. These skills are essential for accurately identifying unusual patterns in data and contributing to an organization's data-driven decision-making processes.

What are typical daily tasks and responsibilities for someone working in Anomaly Detection?

Professionals in Anomaly Detection typically spend their days analyzing large datasets to identify unusual patterns or behaviors that could indicate errors, fraud, or other significant events. They build and maintain models using statistical techniques and machine learning algorithms, validate detected anomalies, and collaborate closely with data engineers, cybersecurity teams, or business analysts depending on the industry. Regular reporting of findings, tuning detection systems for accuracy, and staying updated with emerging methodologies are also important aspects of the job. The role often requires working both independently and as part of a multidisciplinary team to ensure timely and actionable insights are delivered.
More about Anomaly Detection jobs
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 Anomaly Detection jobs? States with the most job openings for Anomaly Detection jobs include:
What job categories do people searching Anomaly Detection jobs look for? The top searched job categories for Anomaly Detection jobs are:
Anomaly Detection jobs near you
Infographic showing various Anomaly Detection job openings in the United States as of May 2026, with employment types broken down into 6% As Needed, 86% Full Time, 1% Part Time, 5% Contract, and 2% Nights. Highlights an 67% Physical, 24% Hybrid, and 9% Remote job distribution, with an average salary of $80,032 per year, or $38.5 per hour.
AI/ML Data Scientist

AI/ML Data Scientist

Wise Skulls

Phoenix, AZ • On-site

Contractor

Posted 8 days ago

Job description

Title: AI/ML Data Scientist
Location: Phoenix, AZ - (100% Onsite)
Duration: 6 months (possibility of an extension)
Implementation Partner: Infosys
End Client: To be disclosed
JD:
Position Overview
  • We are seeking a highly experienced Senior Data Scientist to support and enhance our AIOps (Artificial Intelligence for IT Operations) solution. This position plays a critical role in advancing our anomaly detection, root cause analysis, and intelligent automation capabilities across enterprise systems.
  • The ideal candidate will bring deep expertise in machine learning, statistical modeling, and large-scale data analysis, with strong hands-on proficiency in Python and SQL. This individual will drive innovation in operational intelligence by leveraging anomaly detection, causal reasoning, time series modeling, and emerging GenAI techniques.

Key Responsibilities
  • Design and implement scalable machine learning models for AIOps use cases including anomaly detection and root cause analysis.
  • Develop and optimize advanced anomaly detection algorithms for infrastructure, application, and operational telemetry data.
  • Apply causal reasoning frameworks to identify drivers of incidents and operational disruptions.
  • Build and deploy time series forecasting and modeling solutions to predict performance degradation and system failures.
  • Develop robust data pipelines and analytical workflows using Python and SQL.
  • Integrate Generative AI (GenAI) techniques for intelligent summarization, incident triage, knowledge extraction, and automation.
  • Collaborate with engineering, DevOps, and platform teams to operationalize ML models in production environments.
  • Drive continuous improvement of model performance, scalability, and reliability.
  • Mentor junior data scientists and contribute to best practices in MLOps and model governance.

Required Qualifications
  • 6+ years of experience in data science or applied machine learning roles.
  • Strong communication and stakeholder management skills.
  • Strong proficiency in Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow or similar).
  • Advanced SQL skills for data manipulation and analysis.
  • Proven experience in anomaly detection techniques (statistical, ML-based, deep learning-based).
  • Strong understanding and practical application of causal inference and causal reasoning methodologies.
  • Hands-on experience with large-scale structured and time series datasets.
  • Solid knowledge of time series modeling (ARIMA, Prophet, LSTM, state-space models, etc.).
  • Experience deploying models into production environments.
  • Strong analytical thinking and problem-solving capabilities.

Preferred Qualifications
  • Experience in AIOps, IT Operations analytics, or observability platforms.
  • Exposure to GenAI / LLM-based solutions for operational intelligence.

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