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Fraud Detection Machine Learning Jobs in Colorado

Signifyd

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107K - $147K/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 - $146K/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

$102K - $146K/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 Analytics Engineer

Fort Collins, CO · On-site

$102K - $146K/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 - $146K/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 ...

Iterable

Senior Machine Learning Engineer (Nova)

Denver, CO · On-site

$107K - $147K/yr

They are seeking a Senior Machine Learning Engineer to build core Machine Learning foundations ... detection. • Background in personalization, recommendations, or applied NLP. • Experience ...

BillGO, Inc.

AI Data Scientist

Fort Collins, CO · On-site

$102K - $146K/yr

... and machine learning expertise to help shape the future of data-driven innovation in fintech. You'll work on developing intelligent systems that power risk modeling, fraud prevention, customer ...

BillGO, Inc.

AI Data Scientist

Fort Collins, CO · On-site

... and machine learning expertise to help shape the future of data-driven innovation in fintech. You'll work on developing intelligent systems that power risk modeling, fraud prevention, customer ...

S3 Shared Services

Fraud Analyst

Englewood, CO · Remote

$52K - $60K/yr

... of detection techniques. Document daily workflows using job aids or procedures when needed ... If you join our team, well invest in your learning and development through training programs ...

S3 Shared Services

Fraud Analyst

Englewood, CO · On-site

$52K - $60K/yr

... detection techniques. • Document daily workflows using job aids or procedures when needed. • ... If you join our team, we'll invest in your learning and development through training programs ...

S3 Shared Services

Fraud Analyst

Englewood, CO · Remote

$52K - $60K/yr

... detection techniques. • Document daily workflows using job aids or procedures when needed. • ... If you join our team, we'll invest in your learning and development through training programs ...

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All JobsFraud Detection Machine Learning JobsFraud Detection Machine Learning Jobs in Colorado

Fraud Detection Machine Learning information

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

As of Jul 22, 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 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 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 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
Senior Machine Learning Engineer I // II

Senior Machine Learning Engineer I // II

Signifyd

Denver, CO • On-site, Remote

$107K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 9 days ago

Job description

At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients' success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy.
Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values here!
The Senior Machine Learning Engineer will join our ML team. This team is responsible for building, maintaining, and monitoring the production ML models and offline experimentation frameworks that are at the core of Signifyd's product. This includes the core fraud detection model that decides the majority of our traffic, alongside our model training and evaluation infrastructure. We work closely with Platform Engineering teams to contribute novel modeling methods, advanced feature engineering, and robust statistical practices.
Our Culture
We value tenacity, curiosity, and a hunger for learning. Our adversaries are highly motivated fraudsters looking to exploit any gap. We seek equally motivated individuals who are passionate about keeping our customers safe while pulling the field of adversarial machine learning forward.
The Role
As a Senior Machine Learning Engineer, you will be a driver of technical execution within the ML team. You won't just build models-you'll own the end-to-end lifecycle of high-impact ML projects, from offline experimentation to deployment to production. You will be responsible for improving model performance, refining our experimentation processes, and ensuring our fraud detection systems are robust, scalable, and scientifically sound.
Responsibilities:
  • Expand ML Capabilities - Identify, prototype, and integrate new ML technologies and infrastructure to enhance fraud detection effectiveness and scalability.
  • Enable High-Velocity Experimentation - Own the design and implementation of ML pipeline components that accelerate our innovation
  • Collaborate Across Functions - Partner with Product, Engineering, and Risk teams to translate business requirements into technical solutions and ensure ML initiatives align with customer needs.
  • Raise the Bar - Foster a culture of technical excellence by championing best practices in testing, documentation, model monitoring, and development.

Requirements:
  • Education: A degree in Computer Science, Statistics, or a comparable quantitative field.
  • Experience: 4-6+ years of post-undergrad work experience in a production-grade ML environment.
  • Technical Depth: Strong foundation in machine learning theory, statistical evaluation, and experience with supervised/unsupervised learning at scale.
  • Execution Focus: Proven track record of taking ML projects from research/prototype to high-scale production environments.
  • Communication: Ability to communicate technical findings clearly to both technical peers and non-technical stakeholders.
  • Tech Stack: Proficiency in Python, SQL, key ML libraries, and Spark
  • Mindset: A strong outcome-oriented mindset-you care about the "why" behind the models and the business impact they create.
  • Attention to detail is critical in fraud prevention. To demonstrate this, please start your response to the first application question with the word 'Stochastic'

Nice to have:
  • Previous experience in fraud, fintech, payments, or e-commerce.
  • Passion for writing well-tested production-grade code
  • A Master's Degree or PhD.
Why Join Us?
  • Make an Impact - Your work will directly shape the future of fraud prevention, protecting billions of payments.
  • Lead & Grow - Drive high-visibility initiatives and develop leadership skills in a fast-paced, high-growth environment.
  • Innovate at Scale - Work with cutting-edge ML technologies and experiment freely to push the boundaries of what's possible.
  • Collaborative Culture - Join a team that values curiosity, ownership, and continuous learning.

#LI-Remote
Benefits in our US offices:
  • Discretionary Time Off Policy (Unlimited!)
  • 401K Match
  • Stock Options
  • Annual Performance Bonus or Commissions
  • Paid Parental Leave (12 weeks)
  • On-Demand Therapy for all employees & their dependents
  • Dedicated learning budget through Learnerbly
  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Flexible Spending Account (FSA)
  • Short Term and Long Term Disability Insurance
  • Life Insurance
  • Company Social Events
  • Signifyd Swag

Compensation:
In the United States, each work location is assigned a specific pay zone, which determines the salary range for a given position. The starting base salary for the selected candidate will be based on a variety of factors, including job-related skills, experience, qualifications, geographic location, and current market conditions.
Base Salary Ranges by Pay Zone:
  • Tier 1 (NYC/SF Bay Area/Seattle): $160,000 - $190,000 annually
  • Tier 2 (DC Metro/Austin/Chicago/Denver/Boston/Los Angeles/San Diego):$150,000 - $180,000 annually
  • Tier 3 (US - All Other): $140,000 - $170,000 annually
Equity: This role is eligible for a stock option grant of 4,000 stock options, based on the position level and internal compensation guidelines.
Bonus: This role is eligible for an annual performance bonus of up to 10% of base salary.
We want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
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