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Fraud Detection Machine Learning Jobs in Colorado

Signifyd

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107.60K - $147.70K/yr

The Senior Machine Learning Engineer will join our ML team. This team is responsible for building ... This includes the core fraud detection model that decides the majority of our traffic, alongside ...

BillGO, Inc.

Data Scientist AI/ML

Fort Collins, CO · On-site

$102K - $146.90K/yr

We're looking for a Data Scientist with deep AI and machine learning expertise to help shape the ... By building intelligent models for risk, fraud detection, and payment optimization, the Data ...

BillGO, Inc.

Data Scientist AI/ML

Fort Collins, CO · On-site

$102K - $146.90K/yr

We're looking for a Data Scientist with deep AI and machine learning expertise to help shape the ... By building intelligent models for risk, fraud detection, and payment optimization, the Data ...

True Anomaly

Machine Learning Engineer

Denver, CO · On-site

$85K - $180K/yr

Bachelor's degree in computer science, machine learning, data science, electrical engineering, or a ... Familiarity with classification, regression, clustering, or anomaly detection techniques

True Anomaly

Senior Machine Learning Engineer

Denver, CO · On-site

$155K - $260K/yr

Bachelor's degree in computer science, machine learning, data science, electrical engineering, or a ... Anomaly & outlier detection: statistical, density-based, and deep learning approaches * Object ...

BillGO, Inc.

Data Analytics Engineer

Fort Collins, CO

$102K - $146.90K/yr

... fraud detection and operational efficiency. By bridging the gap between raw data and business ... Data Science and Machine Learning hands-on experience. * Familiarity with event-driven ...

BillGO, Inc.

Data Analytics Engineer

Fort Collins, CO · On-site

$102K - $146.90K/yr

... fraud detection and operational efficiency. By bridging the gap between raw data and business ... Data Science and Machine Learning hands-on experience. * Familiarity with event-driven ...

True Anomaly

Senior Machine Learning Engineer

Denver, CO · On-site

$107.50K - $147.70K/yr

They are seeking a Senior Machine Learning Engineer to design, build, and deploy core machine ... Anomaly & outlier detection: statistical, density-based, and deep learning approaches • Strong ...

Cisco

Principal Machine Learning Engineer

Denver, CO · On-site

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the ... detection, and multi-modality modeling. • Solid proficiency in Python and deep learning ...

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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:
Fraud Detection Machine Learning jobs near you
Director, Fraud Strategy and Operations

Director, Fraud Strategy and Operations

BillGO, Inc.

Fort Collins, CO • On-site

$132.80K - $196.50K/yr

Full-time

Medical, Retirement

Posted 20 days ago

Job description

Director, Fraud Strategy & Operations
Protect the Integrity of Small Business Payments at BillGO
Are you a strategic fraud and risk leader who thrives on solving complex problems, modernizing operations, and building intelligent systems that protect digital payments at scale?
At BillGO, our Director of Fraud Strategy & Operations will lead the evolution of fraud prevention, risk screening, and fraud investigations across the BillGO Exchange platform. This leader will build scalable systems, processes, and teams that protect the platform while enabling fast, simple, and secure payments for our growing network of customers.
This leadership role plays a critical part in supporting BillGO's mission of Making Payments Simple for Small Businesses.
Why This Role Matters
Every customer on the BillGO Exchange platform depends on us to ensure payments move securely and reliably. As the platform grows and transaction volumes scale, protecting the integrity of the ecosystem becomes increasingly important.
As Director of Fraud Strategy & Operations, you will lead the strategy and execution for fraud prevention, fraud detection, fraud investigation, and customer risk screening processes that ensure only trusted participants gain access to the platform. This includes overseeing the operational process for performing preliminary risk and compliance checks on customers registered through the Enrollment team prior to gaining access to BillGO Exchange and processing check payments as virtual card.
Historically, portions of this process have relied heavily on manual review and operational effort. This role will lead the transformation of fraud operations by implementing scalable detection systems, customer authentication & authorization frameworks, fraud screening automation, and transaction monitoring. Artificial intelligence & machine learning will play an important role in improving accuracy, speed, and operational efficiency.
Your leadership will ensure that BillGO Exchange remains a secure and trusted platform while enabling customers to access fast, simple, and reliable digital payments.
What You'll Do
  • Build and Lead the Fraud Strategy: Develop and execute BillGO's fraud prevention and risk management strategy to proactively detect, prevent, and investigate fraudulent activity across the platform.
  • Develop & deploy Customer Transaction Controls: Ensure transaction controls are in place across transaction authorization and transaction posting processes.
  • Oversee BillGO's Customer Authentication & Authorization Framework: Advance the capabilities BillGO leverages to authenticate & authorize customer access to BillGO Exchange business actions/transactions.
  • Modernize Risk Screening and Onboarding Controls: Oversee the process for performing preliminary risk and compliance checks on customers registered through the Enrollment team. Transform historically manual processes into scalable workflows supported by automation and intelligent risk decisioning.
  • Scale Fraud Detection Through AI and Automation: Leverage advanced analytics, machine learning, and automation to improve fraud detection accuracy, accelerate investigations, and reduce operational friction.
  • Strengthen Fraud Operations: Implement scalable investigation workflows, monitoring systems, and operational playbooks to improve fraud detection speed and case resolution efficiency.
  • Lead and Develop the Fraud Team: Build and develop a high-performing fraud operations team responsible for fraud monitoring, investigations, and customer risk screening.
  • Partner Across the Organization: Collaborate closely with Product, Engineering, Data, Risk, Compliance, Enrollment, and Customer Operations teams to embed fraud prevention capabilities into platform workflows.

What You Bring
  • 10+ years of experience in fraud prevention, fraud operations, financial crime, or risk management.
  • 5+ years of leadership experience managing fraud, risk, or financial crime teams.
  • Experience in fintech, payments, or financial services environments with high transaction volumes.
  • Demonstrated success implementing fraud detection technologies, automation, or machine learning models.
  • Experience designing operational risk screening or onboarding verification processes.
  • Strong analytical and problem-solving skills with the ability to translate data insights into operational improvements.
  • Proven ability to collaborate cross-functionally with product, engineering, data, and operations teams.
  • Excellent communication and leadership skills with the ability to influence senior stakeholders.

Compensation
We offer a competitive compensation package commensurate with the experience and qualifications of the selected candidate. This includes base salary, performance-based incentives, and a comprehensive benefits package.
We offer a highly competitive executive compensation package, including:
  • Base Salary: $132,800 - $196,500
  • Performance Incentive
  • Equity Opportunities
  • Comprehensive Benefits: Inclusive of health, retirement, and lifestyle program.

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