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Kyc Machine Learning Jobs (NOW HIRING)

Fin

Risk Analyst

New York, NY · On-site

$100K - $175K/yr

... machine learning and predictive analytics. * Ensure alignment with regulatory requirements, including AML, KYC, and digital asset regulations. * Draft detailed reports and dashboards on risk findings ...

Fin

Risk Analyst

New York, NY · On-site +1

$100K - $175K/yr

... machine learning and predictive analytics. * Ensure alignment with regulatory requirements, including AML, KYC, and digital asset regulations. * Draft detailed reports and dashboards on risk findings ...

Fin

Risk Analyst

New York, NY · Remote

$100K - $175K/yr

... machine learning and predictive analytics. * Ensure alignment with regulatory requirements, including AML, KYC, and digital asset regulations. * Draft detailed reports and dashboards on risk findings ...

Quantifind

Associate Data Scientist

Palo Alto, CA · On-site

$69K - $69K/yr

... KYC), Customer Due Diligence (CDD), Fraud Risk Management, and Anti-Money Laundering (AML ... Members of the Data Science team prototype and build complex Machine Learning solutions, improve ...

Quantifind

Associate Data Scientist

Palo Alto, CA · On-site

$69K - $69K/yr

... KYC), Customer Due Diligence (CDD), Fraud Risk Management, and Anti-Money Laundering (AML ... Members of the Data Science team prototype and build complex Machine Learning solutions, improve ...

Matrix Global

Regional Sales Director

AML / KYC * Digital Trust * Identity and Authentication * Risk Management * AI and Machine Learning * Transaction Monitoring * Cyber / Digital Security * Develop compelling business cases and ...

Matrix-International Financial Services

Financial Crime Fraud Prevention and Detection AML / KYC Digital Trust Identity and Authentication Risk Management AI and Machine Learning Transaction Monitoring Cyber / Digital Security * Develop ...

Sardine

Data Engineer - Onboarding

San Francisco, CA · On-site

$134K - $162K/yr

... machine learning foundation that Sardine's compliance decisions run on. Every onboarding decision we make -- a payment approved, an account blocked, a KYC case escalated -- is the output of a ...

Stride Bank Na

Financial Crimes Model Analyst

Tulsa, OK · On-site

... 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 ...

Sinch

$102K - $130K/yr

Know Your Customer (KYC): Lead the team responsible for evaluating new customers, validating ... or machine learning tools to optimize manual vetting and increase operational speed. * Proven ...

Sinch

WI · On-site

$126K - $162K/yr

Know Your Customer (KYC): Lead the team responsible for evaluating new customers, validating ... or machine learning tools to optimize manual vetting and increase operational speed. * Proven ...

Walmart

Director, Product Management

San Jose, CA · On-site

$169K - $338K/yr

... KYC/KYB capabilities and improving business trustworthiness scoring to prevent fraud. * Strong understanding of seller identity and intent signals that power machine learning risk models for rapid ...

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Kyc Machine Learning information

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How much do kyc machine learning jobs pay per hour?

As of Sep 15, 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.

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.

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.

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 other helpful pages are available for Kyc Machine Learning?

Other pages related to Kyc Machine Learning:

Infographic showing various Kyc Machine Learning job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $44,363 per year, or $21.3 per hour.

Risk Analyst

New York, NY • On-site

Fin
Specialized Design Services • 1 - 10 employees
Learn more about Finexternal

$100K - $175K/yr

Full-time

Re-posted yesterday

Job description

About Fin

Fin is a next-generation payments platform built for high-value, global, and instant transactions. We are a Series A-stage company backed by Sequoia, Circle, and other notable investors. Powered by stablecoins, Fin enables users and businesses to move millions of dollars in seconds - whether to other Fin users, directly into bank accounts, or across crypto rails. By combining the speed of crypto with the reliability and trust of traditional finance, Fin reimagines how money moves worldwide. If banks and payment products were reinvented today, they would look like Fin.

Role Overview

We are hiring our first  Fraud/Risk Analyst to join our Risk & Compliance team . This role will focus on identifying, analyzing, and mitigating risks associated with digital asset transactions – including ACH fraud and compliance with applicable regulations like the Patriot Act and Bank Secrecy Act. This is a critical position, reporting directly to the CEO, and will require a combination of technical, analytical, and regulatory expertise to build a robust fraud detection and risk assessment framework from the ground up.

Key Responsibilities

  • Develop and implement a comprehensive risk management strategy tailored to the evolving digital asset landscape.

  • Take action to resolve automatically flagged transactions and individuals

  • File suspicious activity reports as required 

  • Monitor and analyze transaction data to detect potential fraud, suspicious activities, and emerging risk trends.

  • Utilize advanced data analysis techniques and fraud detection tools to identify anomalies and potential security threats.

  • Create and maintain risk assessment models to evaluate the financial and reputational impact of potential fraud incidents.

  • Partner with the engineering team to design and implement fraud detection systems, leveraging machine learning and predictive analytics.

  • Ensure alignment with regulatory requirements, including AML, KYC, and digital asset regulations.

  • Draft detailed reports and dashboards on risk findings, fraud incidents, and risk mitigation strategies for senior leadership and stakeholders.

  • Lead cross-functional risk assessments for new product launches, ensuring security and fraud prevention measures are integrated into product design.

  • Stay abreast of emerging risks in the digital asset space, including regulatory changes and new fraud tactics.

  • Develop incident response plans for fraud detection and participate in incident response drills to assess and enhance our risk management framework.

Qualifications

  • Bachelor's degree in Finance, Economics, Computer Science, Data Science, or related field.

  • 5+ years of experience in fraud analysis, risk management, or financial crime prevention, ideally within fintech, digital assets, or blockchain environments.

  • Demonstrated experience with fraud detection systems, transaction monitoring tools, and data analysis platforms (SQL, Python, R).

  • Strong knowledge of digital asset platforms, blockchain technology, and stablecoin ecosystems.

  • Experience with regulatory compliance, particularly regarding AML, KYC, and financial crime prevention.

  • Exceptional analytical and problem-solving skills with a data-driven approach to decision-making.

  • Strong written and verbal communication skills, with the ability to clearly articulate complex risk findings to non-technical stakeholders.

Preferred Qualifications

  • Certifications such as Certified Fraud Examiner (CFE), Certified Risk Manager (CRM), or CAMS.

  • Experience with machine learning models for fraud detection and predictive analytics.

  • Familiarity with incident response protocols and risk mitigation frameworks in financial services.

  • Prior experience in a fast-paced startup or scaling fintech environment.

Compensation Range: $100K - $175K