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Crime Analyst Jobs in Utah (NOW HIRING)

Akima, LLC

Intelligence Analyst III

Riverton, UT · On-site

... criminal and civil investigations. * Provide written results within formal and informal briefings ... Utilize a variety of financial analysis software to include ACTIONABLE INTELLIGENCE TECHNOLOGIES ...

Ascensus

Senior Fraud Strategy Analyst

Salt Lake City, UT · On-site

$100 - $150/hr

Experience in fraud and/or financial crime roles within banking, financial services, fintech ... Experience analyzing fraud rule performance and using data to assess outcomes, validate results ...

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Crime Analyst information

See Utah salary details

$30K

$59.2K

$92.4K

How much do crime analyst jobs pay per year?

As of Sep 5, 2026, the average yearly pay for crime analyst in Utah is $59,179.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,100.00 and $71,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a crime analyst?

To thrive as a Crime Analyst, you need a solid background in criminology, data analysis, and statistical methods, often supported by a relevant degree such as criminal justice or statistics. Familiarity with analytical software (like GIS, Excel, or crime mapping tools) and sometimes certifications in crime analysis or law enforcement databases are commonly required. Strong critical thinking, attention to detail, and effective communication enable analysts to interpret complex data and present actionable insights to law enforcement agencies. These skills are crucial for identifying crime trends, supporting investigations, and informing strategic decisions to improve public safety.

How do crime analysts typically collaborate with law enforcement officers and investigators?

Crime Analysts work closely with law enforcement officers and investigators by providing data-driven insights to support ongoing cases and proactive policing efforts. They analyze crime reports, identify patterns or trends, and present findings in meetings or briefings, often using maps and visual aids. Effective communication and teamwork are essential, as analysts must translate complex data into actionable intelligence that helps officers make informed decisions and prioritize resources. Regular collaboration ensures that analytical findings directly support field operations and investigative strategies.

What is the difference between Crime Analyst vs Crime Scene Investigator?

AspectCrime AnalystCrime Scene Investigator
CredentialsBachelor's degree in criminal justice, criminology, or related field; often requires certificationHigh school diploma or equivalent; specialized training or certification often preferred
Work EnvironmentOffice setting, analyzing data and crime patternsCrime scenes, laboratories, outdoor locations
Employer & IndustryLaw enforcement agencies, government officesPolice departments, forensic labs
Primary FocusAnalyzing crime data, identifying trends, supporting investigationsCollecting, documenting, and analyzing physical evidence from crime scenes

While both roles support law enforcement, Crime Analysts focus on data analysis and pattern recognition, working mainly in offices. Crime Scene Investigators handle physical evidence collection and scene processing, often working outdoors or at crime scenes. Understanding these differences helps in choosing the right career path or job search focus.

How much do crime analysts make?

Crime analysts typically earn an average annual salary of around $55,000 to $75,000, depending on experience, education, and location. Entry-level positions may start lower, while experienced analysts with specialized skills or certifications can earn higher salaries. Salaries can also vary based on the size of the agency and the complexity of the role.

Is a crime analyst a hard job?

A crime analyst's job involves analyzing crime data, creating reports, and supporting law enforcement strategies, which requires strong analytical skills and attention to detail. The role can be demanding due to the need for accuracy, working with large datasets, and sometimes working under tight deadlines or irregular hours.
More about Crime Analyst jobs

What are the most commonly searched types of Crime Analyst jobs in Utah?

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For Crime Analyst jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Crime Analyst jobs in Utah look for?

The top searched job categories for Crime Analyst jobs in Utah are:

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Cities in Utah with the most Crime Analyst job openings:

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Crime Analyst jobs near you
Infographic showing various Crime Analyst job openings in Utah as of August 2026, with employment types broken down into 83% Full Time, 11% Part Time, and 6% Contract. Highlights an 81% Physical, 8% Hybrid, and 11% Remote job distribution, with an average salary of $59,179 per year, or $28.5 per hour.

Financial Crimes Model Analyst

STRIDE BANK NA

Salt Lake City, UT

Full-time

Posted 3 days ago

New

Job description

The Financial Crimes Model Analyst plays a critical role in designing, validating, and optimizing analytical models that support financial crime prevention, including fraud, AML/KYC, and sanctions monitoring. This role leverages modern data-agnostic, low/no-code analytical platforms and machine-learning tooling to operationalize robust detection logic, integrate LLM/SLM outputs responsibly, and ensure alignment with Model Risk Management (MRM) standards.

PRINCIPAL DUTIES AND RESPONSIBILITIES

  1. Designs, validates, and enhances financial crime detection models across fraud, AML/KYC screening, and related domains.
  2. Applies statistical techniques to evaluate and calibrate LLM/SLM outputs when used in decision-support workflows.
  3. Conducts ablation studies, back testing, and reproducible experiments to ensure model stability and business impact.
  4. Optimizes model and pipeline efficiency, including latency, throughput, and computational performance.
  5. Develops, tracks, and interprets performance metrics.
  6. Implements monitoring for drift, bias, degradation, and shifts.
  7. Produces audit-ready MRM documentation, including validation plans, governance artifacts, explainability notes, and calibration reports.
  8. Maintains model health dashboards and reporting for executives, governance bodies, and oversight functions.
  9. Partners with internal and external data engineers and vendor partners to maintain reliable inputs and production workflows.
  10. Develops SQL and Python assets for exploration, experimentation, reporting, and automated artifact generation.
  11. Maintains clear and comprehensive documentation, including data dictionaries, model cards, decision logic, and workflow diagrams.
  12. Works cross-functionally with engineering, product, compliance, risk, and vendor teams to deploy and maintain models.
  13. Translates complex analytical concepts into accessible insights for varied technical and business audiences.

Non-Essential Functions: Performs other duties as assigned.

EDUCATION AND/OR EXPERIENCE

  • Bachelor's degree in Statistics, Econometrics, Data Science, Mathematics, Computer Science, or a related quantitative field, required; Master's degree, preferred.
  • 3-5 years' experience in model development, evaluation, monitoring, risk governance, or model lifecycle management supporting BSA/AML compliance, fraud and/or case investigation, or experience in quality assurance/control or internal audit, required.
  • Hands-on expertise in SQL and Python for analysis and rapid prototyping, required.
  • Familiarity with modern modeling techniques, or similar low/no-code platforms, and the responsible use of LLM/SLM capabilities, required.
  • Experience producing governance-grade validation or audit documentation, required.
  • Exposure to financial crime domains (AML, KYC, fraud), preferred.
  • CAMS and/or CAFP certifications, preferred.

KNOWLEDGE, SKILLS, AND ABILITIES

  • Strong understanding of supervised/unsupervised ML evaluation, calibration, drift detection, and explainability methods.
  • Knowledge of data quality domains and data lineage principles.
  • Familiarity with AI model governance concepts, including MRM standards and regulatory expectations.
  • Ability to develop and maintain dashboards and report for model health and risk indicators.
  • Knowledge of regulatory environment(s) and emerging BSA/AML and fraud trends.
  • Strong investigative, written, and oral communication skills.
  • Thorough and detail-oriented.
  • Strong commitment to ethics, and the ability to understand a variety of issues and perspectives.
  • Understanding of the banking industry, including bank partnerships with fintech companies.
  • Multitasks effectively and takes action promptly, both independently and in a team environment.
  • Handles highly confidential information with appropriate discretion, and works well in a high volume, fast paced environment.

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