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Anomaly Detection Jobs (NOW HIRING)

Soteria Reinsurance Ltd.

Support anomaly detection efforts to identify coordinated fraud attacks and organized fraud rings. * Communicate insights clearly and effectively to influence stakeholders and drive product changes.

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 ...

Syntricate Technologies

AI With SRE

Austin, TX · On-site

$56.50 - $75/hr

The role involves automating client models, anomaly detection, and requires extensive experience in Python, Kubernetes, and various monitoring tools. Responsibilities : • 10+ yrs of total ...

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Anomaly Detection information

What is anomaly detection?

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 does someone working in anomaly detection do?

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.

What are the key skills and qualifications needed to thrive in anomaly detection?

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.

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Anomaly Detection jobs near you
Infographic showing various Anomaly Detection job openings in the United States as of September 2026, with employment types broken down into 2% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Manager, Fraud Detection and Analytics

Durham, NC • On-site

Fidelity Investments
Investment Management and Consulting Services • 10K+ employees
Learn more about Fidelity Investmentsexternal

Full-time

Posted 17 days ago

Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 274 frontline employees who took The Breakroom Quiz

Job description

Job Description:

Note: Fidelity will not provide immigration sponsorship for this position.

The Role

In this role, you will work closely with data scientists, fraud strategists, and business stakeholders to support real-time fraud detection and prevention strategies. Your work will focus on identifying payment card fraud schemes and implementing detection solutions to mitigate risk, using advanced analytics and data analysis tools.

Key Responsibilities:

  • Analyze complex datasets to identify risk signals related to fraudulent debit card transactions.
  • Use Python, SQL, and analytical tools to analyze large, complex datasets and extract actionable insights.
  • Implement fraud detection strategies in a real-time fraud decisioning engine.
  • Support anomaly detection efforts to identify coordinated fraud attacks and organized fraud rings.
  • Communicate insights clearly and effectively to influence stakeholders and drive product changes.
  • Collaborate across business units to drive data-informed strategies for fraud detection.
  • Contribute to the continuous improvement of the fraud detection program, through rule and model refinement, fraud hunting, and data discovery.

The Expertise and Skills You Bring

  • Bachelor's with 5 plus years or Master's with 3 plus years of experience in data analytics, preferably in fraud detection, cybersecurity, or risk domains.
  • Strong proficiency in Python and SQL for data analysis and automation.
  • Experience working with large-scale datasets and analytical platforms.
  • Skilled in using analytics tools (e.g., dashboards, statistical packages, data visualization platforms) to perform advanced analytics and uncover actionable insights.
  • Familiarity with payment card fraud detection and risk management.
  • Ability to translate complex data into clear, actionable insights.
  • Strong communication and collaboration skills to work across teams and influence decisions.
  • Experience in anomaly detection or fraud analytics is a plus.

The Team

The Fraud Detection Analytics Team is responsible for ensuring that fraudulent events-such as account logins, account openings, and payment attempts-occurring on Fidelity's platform are detected and mitigated in a timely manner. The team leverages a combination of vendor and internally developed tools and models to enable real-time detection and interdiction at various stages of the customer lifecycle.

Fidelity's Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Certifications:Category:Data Analytics and Insights

Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

What Fidelity Investments employees say

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