1

Kyc Machine Learning Jobs (NOW HIRING)

... KYC/KYB, underwriting, transaction monitoring, fraud detection and remediation, and credit risk scoring * Experience with automation for risk, including automated scoring, machine learning, data ...

Investor Services Manager

Dallas, TX ยท On-site +1

$130K - $140K/yr

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... KYC) and optional training. Additional client-specific training is provided by the supervisor and ...

Investor Services Manager

New York, NY ยท On-site +1

$130K - $140K/yr

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... KYC) and optional training. Additional client-specific training is provided by the supervisor and ...

Investor Services Manager

Raleigh, NC ยท On-site +1

$130K - $140K/yr

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... KYC) and optional training. Additional client-specific training is provided by the supervisor and ...

Investor Services Manager

New York, NY ยท On-site

$130K - $140K/yr

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... KYC) and optional training. Additional client-specific training is provided by the supervisor and ...

Fraud Specialist

Phoenix, AZ ยท On-site +1

$22.50/hr

... KYC documentation, external search engines and open-source websites) to determine level of risk ... Monitor and utilize AI fraud detection tools, machine learning model scores, and alert systems to ...

Fraud Specialist

Phoenix, AZ ยท On-site +1

... KYC documentation, external search engines and open-source websites) to determine level of risk ... Monitor and utilize AI fraud detection tools, machine learning model scores, and alert systems to ...

New

Fraud Specialist

Phoenix, AZ ยท On-site

$22.50/hr

... KYC documentation, external search engines and open-source websites) to determine level of risk ... Monitor and utilize AI fraud detection tools, machine learning model scores, and alert systems to ...

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... Ensure appropriate AML/KYC documentation is provided by investors. * Ensure appropriate FATCA/CRS ...

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... Review AML/KYC documentation provided by investors and follow-up where necessary. Escalate to ...

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... Review AML/KYC documentation provided by investors and follow-up where necessary. Escalate to ...

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... Review AML/KYC documentation provided by investors and follow-up where necessary. Escalate to ...

next page

Showing results 1-20

Kyc Machine Learning information

See salary details

$14

$21

$25

How much do kyc machine learning jobs pay per hour?

As of Jun 24, 2026, the average hourly pay for kyc machine learning in the United States is $21.33, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $22.84 per hour, depending on experience, location, and employer.

What is a KYC Machine Learning specialist?

A KYC (Know Your Customer) Machine Learning specialist is a professional who uses artificial intelligence and data science techniques to automate and enhance the process of verifying customer identities and detecting suspicious activities in financial services. Their work involves building and maintaining models that analyze vast amounts of customer data, flagging potential risks or compliance issues. By leveraging machine learning, these specialists help organizations improve efficiency, reduce false positives, and stay compliant with regulatory requirements.

What is the difference between Kyc Machine Learning vs Kyc Analyst?

AspectKyc Machine LearningKyc Analyst
Required CredentialsData Science, Machine Learning certifications, programming skillsFinancial analysis, compliance certifications, attention to detail
Work EnvironmentData-driven, technical, often in tech or finance firmsFinancial institutions, compliance departments, customer review
Employer & Industry UsageFintech, banking, tech companies implementing automated KYC processesBanking, financial services, regulatory compliance teams

While Kyc Machine Learning focuses on developing algorithms to automate and improve KYC processes, Kyc Analysts perform manual reviews and ensure compliance. Both roles are essential in the KYC ecosystem, with the machine learning role emphasizing technical development and the analyst role emphasizing manual verification and compliance oversight.

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

To thrive as a KYC Machine Learning Specialist, you need a solid foundation in data science, machine learning algorithms, and knowledge of financial regulations, often supported by a degree in computer science, statistics, or a related field. Familiarity with Python, SQL, machine learning frameworks (such as TensorFlow or Scikit-learn), and experience with compliance systems or anti-money laundering (AML) platforms is typically required. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for translating complex technical findings into actionable insights for compliance teams. These skills ensure the development of robust, accurate models that enhance regulatory compliance and risk detection in financial institutions.

How does a KYC Machine Learning specialist typically collaborate with compliance and data teams?

As a KYC Machine Learning specialist, you'll work closely with compliance teams to understand regulatory requirements and ensure that machine learning models align with legal standards. You'll also collaborate with data engineers and analysts to source, clean, and structure data for model training and validation. Regular cross-functional meetings are common to discuss model performance, address false positives/negatives, and implement feedback from compliance officers, ensuring that solutions are both effective and regulatorily compliant.
Infographic showing various Kyc Machine Learning job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $44,363 per year, or $21.3 per hour.

Senior Fraud Strategy and Analytics Manager

Raisin

Lehi, UT โ€ข Hybrid

Other

Medical, Dental, Vision, Retirement, PTO

Posted 3 days ago


Job description

Team

The Risk and Fraud Operations team plays a central role in safeguarding Raisin's business by monitoring, assessing, and mitigating risks across all operational areas. We are responsible for managing fraud prevention, detection and mitigation, investigations and recoveries, monitoring for financial crime events (AML, KYC) and implementing effective risk controls to support the company's growth. Our work bridges business, compliance, and technology-analyzing data, processes, and transactions to identify potential threats while also enabling smooth and secure customer experiences.
We collaborate closely with cross-functional teams (Product, Compliance, Customer Service, and Engineering) to design and execute risk and fraud management frameworks, enhance operational efficiency, and maintain a strong culture of accountability.
Your Responsibilities
As the Senior Fraud Strategy and Analytics Manager, you will be the driving force behind our fraud defense system. We are looking for a proven analytical mind from the financial services sector who can challenge our current thinking, build predictive fraud models, redesign existing fraud models, framework and processes.ย Using SQL, Python/R Ecosystems, Feature Engineering, you will dissect fraud trends, build predictive models from scratch, and implement sharp, real-time rules to prevent and detect fraud across our payment rails.ย 
This role reports to the Head of Risk and Fraud Operations and requires a highly capable and entrepreneurial individual who can balance deep technical hands-on execution with high-level strategy.

  • Advanced Fraud Strategy & Analytics
    - Uncover Trends: Conduct complex data analysis using SQL, Python and Feature Engineering to proactively identify emerging fraud patterns and system vulnerabilities before they impact the platform.
    - Deploy Fraud Rules: Design, test, and implement robust fraud prevention rules that successfully catch bad actors while maintaining a seamless experience for real customers.
    - Drive Strategy: Elevate Raisin US's capabilities by introducing industry best practices, new methodologies, and innovative fraud prevention strategies that we aren't using today.
    - KPIs & Dashboards: Build out data-driven dashboards to track fraud metrics, losses, and mitigation performance, presenting actionable findings directly to leadership.
  • Model Development & Maintenance
    - Build Predictive Models: Design, build, and deploy machine learning and predictive models utilizing Python to detect anomalies across the entire customer journey (onboarding, funding, and money movement).
    - Feature Engineering: Develop model features based on identity, device, behavioral, and transactional data.
    - Cross-Functional Delivery: Partner closely with Product and Engineering to integrate these models into our real-time production pipelines.
  • AML & Financial Crime Collaboration
    - Risk Profiling: Partner with the Compliance team to enhance customer risk profiling, transaction monitoring, and KYC/AML workflows.
    - Design low-friction, custom risk rules for identity verification, account takeover protection, and transaction monitoring.
    - Continuous Back-Testing: Routinely stress-test current rules against changing regulatory standards and evolving financial crime tactics.

Your Profile

  • Financial Services Background: 8+ years of experience in fraud risk management, analytics, or financial crime specifically within fintech, retail banking, or digital payments.
  • Master of Analytics: Exceptional analytical capabilities are your biggest asset. You love diving into raw data to solve complex puzzles.
  • Technical Stack: Highly proficient in SQL and Python for data manipulation, analytics, and building predictive models. Experience building out fraud dashboards is a must.
  • Payment System Domain Expertise: Deep understanding of Deposits and ACH is required; direct experience with modern instant payment systems like RTP and FedNow is highly preferred.
  • Rule & Model Builder: Proven track record of designing custom fraud rules and deploying machine learning or statistical models in a live environment.

Join our mission, join our team - and grow with us!

At Raisin, we care about each other and it is one of our top priorities to foster an open and caring environment in which everyone feels welcome and comfortable. Our culture is strongly driven by our ambitious team, which connects more than 75 different nationalities.

As part of our team, you will benefit from:

  • Flexible working hours and up to 28 days PTO accrued from your first month, plus 13 public holidays.
  • Employee Development Budget of $2,200 and 4 full training days per year.
  • Company 401k contribution of 5%.
  • Healthcare coverage contribution, including medical, dental and vision.
  • Commuter benefits and flexible working from home policy.
  • Regular team events and yearly Summer and Winter Party.