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Fraud Detection Machine Learning Jobs in Colorado

Principal Machine Learning Engineer

Denver, CO · On-site

$291.50K - $369.10K/yr

Advanced Anomaly Detection - Experience creating robust, scalable approaches (statistical, deep learning, or hybrid) for highvolume, realtime logs data. * MultiModal AI Modeling - Strong track record ...

New

Sr. Machine Learning Software Engineer

Denver, CO · On-site +1

$126.10K - $166.20K/yr

About the Opportunity We are seeking a senior machine learning software engineer to design, build ... Build and maintain model serving infrastructure including monitoring, drift detection, automated ...

Sr. Machine Learning Software Engineer

Denver, CO · On-site

$126.10K - $166.20K/yr

About the Opportunity We are seeking a senior machine learning software engineer to design, build ... Build and maintain model serving infrastructure including monitoring, drift detection, automated ...

Senior AI/ML Architect

Littleton, CO · On-site

$66 - $88.25/hr

... fraud detection) • Build real‑time data processing frameworks to support high‑volume ... culture of experimentation, continuous learning, and cross‑functional collaboration ...

... machine learning, and data engineering methods to cybersecurity use cases such as detection engineering, threat hunting, and response acceleration • Working with cyber data platforms, cloud ...

New

Lead Data Scientist

Centennial, CO · On-site

$117.60K - $206K/yr

... detection, and natural language processing required. Demonstrated advanced knowledge of data science methodologies, statistical modeling, machine learning, and generative AI techniques required.

... detection, and natural language processing required. * Demonstrated advanced knowledge of data science methodologies, statistical modeling, machine learning, and generative AI techniques required.

... detection/classification, natural language processing, reinforcement learning, and large language ... MS or PhD in machine learning, computer science, mathematics, or relevant fields * Experience ...

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Fraud Detection Machine Learning information

See Colorado salary details

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How much do fraud detection machine learning jobs pay per hour?

As of May 30, 2026, the average hourly pay for fraud detection machine learning in Colorado is $18.98, according to ZipRecruiter salary data. Most workers in this role earn between $15.67 and $20.24 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Fraud Detection Machine Learning Specialist, and why are they important?

To thrive as a Fraud Detection Machine Learning Specialist, you need strong expertise in machine learning, statistical analysis, and programming languages like Python or R, typically supported by a degree in computer science, data science, or a related field. Familiarity with tools such as TensorFlow, Scikit-learn, SQL databases, and experience with big data platforms or cloud services is highly valuable. Critical thinking, attention to detail, and effective communication are crucial soft skills for identifying complex fraud patterns and collaborating with interdisciplinary teams. These competencies are vital for developing accurate models that protect organizations from financial losses and maintain trust with customers.

What are some common challenges faced by professionals working in Fraud Detection Machine Learning, and how can they be addressed?

Professionals in Fraud Detection Machine Learning often face challenges such as dealing with highly imbalanced datasets, rapidly evolving fraud patterns, and the need for real-time detection. Managing data imbalance requires careful selection of evaluation metrics and specialized algorithms. Staying ahead of new fraud tactics involves continuous model retraining and close collaboration with domain experts. Additionally, integrating machine learning solutions with existing systems often requires cross-functional teamwork with IT, security, and compliance teams.

What is fraud detection using machine learning?

Fraud detection using machine learning involves leveraging algorithms and data analysis techniques to identify suspicious or fraudulent activities in various domains, such as banking, e-commerce, or insurance. These systems analyze large volumes of transaction data to detect patterns or anomalies that may indicate fraud. Machine learning models can adapt over time, improving their accuracy as they are exposed to more data. This approach helps organizations automate and enhance their ability to prevent, detect, and respond to fraudulent behavior efficiently.

What is the difference between Fraud Detection Machine Learning vs Fraud Analyst?

AspectFraud Detection Machine LearningFraud Analyst
CredentialsData science, machine learning certifications, programming skillsFinance, criminal justice degrees, analytical skills
Work EnvironmentData-driven, tech-focused, often in financial or e-commerce sectorsInvestigative, report-focused, in financial institutions or insurance companies
Employer & IndustryTech companies, banks, e-commerce platformsFinancial institutions, insurance firms, retail

Fraud Detection Machine Learning involves developing algorithms to identify fraudulent activities automatically, relying heavily on data analysis and programming. Fraud Analysts manually investigate suspicious cases and interpret data insights. While both roles aim to prevent fraud, Machine Learning specialists focus on building models, whereas Fraud Analysts focus on case investigation and decision-making.

What are popular job titles related to Fraud Detection Machine Learning jobs in Colorado? For Fraud Detection Machine Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Fraud Detection Machine Learning jobs in Colorado look for? The top searched job categories for Fraud Detection Machine Learning jobs in Colorado are:
What cities in Colorado are hiring for Fraud Detection Machine Learning jobs? Cities in Colorado with the most Fraud Detection Machine Learning job openings:

Senior Machine Learning Engineer with Security Clearance

True Anomaly. Inc.

Denver, CO

$155K - $260K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 12 days ago


Job description

Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it. OUR MISSION True Anomaly delivers decisive capabilities for space superiority.

We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors - enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground. OUR VALUES * Be the offset.

We create asymmetric advantages with creativity and ingenuity. * What would it take? We challenge assumptions to deliver ambitious results.

* It's the people. Our team is our competitive advantage and we are better together. YOUR MISSION As a member of the Applied Algorithms and Autonomy team, you will design, build, and deploy core machine learning and AI capabilities for True Anomaly.

You will work with a talented cross-functional team to advance technology at the intersection of artificial intelligence, machine learning, and data-driven decision-making. This will involve hands-on development across areas including object classification and discrimination, anomaly detection, and threat assessment. You are a first-principles engineer who takes ownership of the systems you build and delivers results.

RESPONSIBILITIES * Design, implement, and test ML/AI models that support threat assessment, object discrimination, and decision-making in operationally relevant environments * Own the full ML development lifecycle - from data ingestion and feature engineering through model training, evaluation, and production deployment * Collaborate with cross-functional teams to translate operational requirements into robust, production-ready ML capabilities * Establish and maintain rigorous model evaluation practices to ensure reliability and performance in real-world conditions * Write clean, well-documented, and testable code in support of AI/ML capabilities QUALIFICATIONS * Bachelor's degree in computer science, machine learning, data science, electrical engineering, or a similar discipline * Proficient in Python * Solid understanding of statistics, probability, and optimization * Experience with ML frameworks such as PyTorch, TensorFlow, or JAX * 4+ years of experience designing, training, and deploying ML models in real-world systems * Demonstrated ability to work in a multidisciplinary team and solve complex problems from first principles * Passion for spaceflight and advancing capabilities related to space domain awareness and space security PREFERRED SKILLS AND EXPERIENCE * Master's or PhD in machine learning, computer science, data science, or a related discipline * Strong background in one of the following core ML disciplines: * Anomaly & outlier detection: statistical, density-based, and deep learning approaches * Object discrimination: multi-class and fine-grained classification, metric learning, few-shot learning, evidential reasoning and Dempster-Shafer Theory (DST) for belief combination and conflict resolution under uncertain or incomplete sensor data * Unsupervised learning: clustering, dimensionality reduction, generative modeling * Sequential and temporal modeling: time-series analysis and sequential modeling * Experience deploying models to edge or resource-constrained environments with real-time processing requirements * Familiarity with space domain data such as space object catalog data, observational data, or RSO characterization * Experience with MLOps tooling: experiment tracking (MLflow, W&B), model versioning, CI/CD for ML pipelines * Background in model interpretability, uncertainty quantification, or safety-critical ML validation COMPENSATION * Base Salary: $155,000 - $260,000 * Equity + Benefits including Health, Dental, Vision, HRA/HSA options, PTO and paid holidays, 401K, Parental Leave Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience. ADDITIONAL REQUIREMENTS * Work Location- this is a fully onsite role. Candidates must be based in or able to commute to our Denver or Long Beach office daily.

* Work environment-the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job. * Physical demands-the physical demands of the job, including bending, sitting, lifting and driving. This position will be open until it is successfully filled.

To submit your application, please follow the directions below. #LI-Onsite To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S.

citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.

True Anomaly is committed to equal employment opportunity on any basis protected by applicable state and federal laws. If you have a disability or additional need that requires accommodation, please do not hesitate to let us.