ZipRecruiter

Log In

1

From Home Anomaly Detection Jobs (NOW HIRING)

Rain

Machine Learning Engineer - Fraud Risk

New York, NY · On-site

$50K/yr

Architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral ... If you feel comfortable at home, please work from home. If you'd like to work with others in an ...

PlayStation Global

Software Engineer II

Los Angeles, CA · Hybrid

$172K - $225K/yr

... and anomaly-detection techniques, including fraud detection and risk scoring to surface usage ... Telecommuting and/or working from home may be permissible pursuant to company policies. Please ...

next page

Showing results 1-20

All JobsAnomaly Detection JobsFrom Home Anomaly Detection Jobs

From Home Anomaly Detection information

See salary details

$14

$21

$40

How much do from home anomaly detection jobs pay per hour?

As of Jul 29, 2026, the average hourly pay for from home anomaly detection in the United States is $21.09, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $21.63 per hour, depending on experience, location, and employer.

What is the 3 month rule for jobs?

The 3 month rule in jobs like from home anomaly detection often refers to a probation or trial period lasting three months, during which employers assess an employee's performance and fit for the role. This period may influence ongoing employment, benefits, or opportunities for permanent hire, and is common in remote or specialized positions requiring specific skills and tools.

What jobs pay $700 a day?

In the field of anomaly detection and related data analysis roles, some freelance or consulting positions can pay around $700 per day, especially for experienced professionals with specialized skills in machine learning, statistical analysis, or data engineering. These roles often require strong technical expertise, familiarity with tools like Python or R, and sometimes certification or advanced degrees. Compensation varies based on experience, project scope, and industry demand.

How to make $1000 a week remotely?

A From Home Anomaly Detection role can contribute to earning $1000 a week remotely by working on data analysis, developing detection models, and utilizing skills in machine learning and programming. Achieving this income level typically requires consistent work, relevant experience, and possibly multiple projects or clients, often within flexible schedules. Building a strong portfolio and gaining certifications in data science or related fields can improve earning potential.

How to make 2000 a week working from home?

To earn $2000 a week as a From Home Anomaly Detection professional, you typically need to work multiple freelance or contract projects, develop specialized skills in data analysis and machine learning, and build a strong reputation. High-paying roles often require experience, certifications, and proficiency with tools like Python, R, or anomaly detection platforms, and may involve flexible or full-time schedules.
More about From Home Anomaly Detection jobs
What cities are hiring for From Home Anomaly Detection jobs? Cities with the most From Home 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 From Home Anomaly Detection jobs? States with the most job openings for From Home Anomaly Detection jobs include:
What job categories do people searching From Home Anomaly Detection jobs look for? The top searched job categories for From Home Anomaly Detection jobs are:
From Home Anomaly Detection jobs near you
Infographic showing various From Home Anomaly Detection job openings in the United States as of July 2026, with employment types broken down into 4% As Needed, 92% Full Time, 1% Part Time, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $43,861 per year, or $21.1 per hour.

Research Fall 2026 Internship/Co-op -Early Anomaly Detection & Intervention

FM

Norwood, MA • On-site

$35/hr

Full-time

Posted 10 days ago

Job description

FM is a leading property insurer of the world's largest businesses, providing more than one-third of FORTUNE 1000-size companies with engineering-based risk management and property insurance solutions. FM helps clients maintain continuity in their business operations by drawing upon state-of-the-art loss-prevention engineering and research; risk management skills and support services; tailored risk transfer capabilities; and superior financial strength. To do so, we rely on a dynamic, culturally diverse group of employees, working in more than 100 countries, in a variety of challenging roles.
Data centers are experiencing unprecedented demands in power density driven by AI and high-performance computing workloads. In contrast to the modern development, traditional fire detection systems are designed to detect fires only after combustion has already occurred, creating a need for earlier anomaly detection methods capable of identifying precursors to thermal runaway, electrical faults, overheating, insulation degradation, arc events, and other incipient fire conditions.
This internship will investigate and evaluate advanced approaches for early anomaly detection and intervention in data center environments. The selected intern will conduct experimental and modeling research to characterize pre-fire signatures and assess potential intervention strategies before ignition or fire development.
Key Responsibilities
  • Conduct literature reviews, including internal reports and external publications.
  • Execute experimental test programs and collect high-quality data. The focus will be designing and building laboratory-scale experimental apparatus to simulate data center equipment faults and pre-fire conditions.
  • Develop models, correlations, and analytical techniques to interpret experimental results.
  • Document findings through technical reports, presentations, and research publications.

Qualifications
Location: Norwood, MA
Duration: 3-6 months starting from September 2026
Education Level: Ph.D. student in Fire Protection Engineering, Mechanical Engineering, Chemical Engineering, or related fields.
Required
  • Strong experimental and analytical skills.
  • Ability to independently design experiments and troubleshoot laboratory setups.
  • Experience with data analysis using Python, MATLAB, R, or similar tools.
  • Strong technical writing and communication skills.

Preferred
  • Experience in building experimental apparatus and integrating sensors with data acquisition systems.
  • Experience with statistical modeling, predictive analytics, or physics-based modeling.

This is an in-office role based in Norwood, MA. Temporary relocation support provided for selected qualified candidate.
FM is an Equal Opportunity Employer and is committed to attracting, developing, and retaining a diverse workforce.
FM logo

About FM

Sourced by ZipRecruiter

Industry

Plastics product manufacturing

Company size

51 - 200 Employees

Headquarters location

Rogers, AR, US

Year founded

1980

Social media

Facebook

View All FM Jobs

Apply