HI
customer data scientist aml fraud
- Salary
- $150K–$225KUSD per year
- Hiring from
- United States
- Work type
- Remote
- Posted
- Sep 27, 2026
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26 days ago
Customer Data Scientist (AML/Fraud)
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150 000 - 225 000$
Work format
remote (only USA)
Work type
fulltime
Grade
senior
b2
Country
US
pythonsqlfraud detectionmachine learningamlbacktestingtransaction monitoringexplainable aicustomer facing consulting
Vacancy from Hirify Global, list of international tech companies
Plus is required to make matches and apply
Plus is required to make matches and apply
$150k-225k/yr
$170k$200kmedian$220k
Similar roles (44) ~ $200k/yr
On CIS market: $4.3k/mo ($3.9k - $10k)
70
Good job
The role is well-defined with a clear focus on AML and fraud detection, but the salary is below market median, which could limit its attractiveness.
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Hirify AI/Original
TL;DR
Customer Data Scientist (AML/Fraud) (Python/SQL): Tuning and validating AML and fraud detection models against customers’ live transaction data with an accent on transaction monitoring, false-positive reduction, and regulatory defensibility. Focus on investigating missed cases and alert quality, presenting model decisions to compliance stakeholders, and translating detection performance into measurable investigator productivity and business value.
Location: United States; remote
Salary: $150,000–$225,000 per year
Company
hirify.global provides AI-supported anti-money laundering and fraud detection technology that combines traditional rules with explainable AI for banks and payment providers.
What you will do
- Tune and optimize AML and fraud detection models and thresholds using customers’ live transaction data.
- Investigate missed cases, alert quality, pattern drift, and detection performance, converting findings into model or configuration changes.
- Build customer-facing analyses showing detection improvements, investigator productivity gains, and false-positive cost reduction.
- Present findings to customer risk, compliance, and data science stakeholders and explain model decisions.
- Partner with Customer Value Partners on account strategy, value realization, and renewal opportunities.
- Document tuning decisions, perform backtesting and sample reviews, and feed systemic findings back into product and model functions.
Requirements
- 5–7 years of experience as a customer-facing data scientist presenting analysis and defending model decisions.
- Required experience in AML, fraud detection, or financial crime analytics, including transaction monitoring and relevant typologies.
- Strong hands-on skills with Python, SQL, and production machine learning tooling.
- Ability to communicate technical findings to risk, compliance, and data science stakeholders.
- Experience translating model performance into business value, including investigator hours saved and false-positive cost avoided.
- Must be based in the United States.
Nice to have
- Experience in transaction monitoring or payments fraud detection at a bank, payment provider, or vendor serving them.
- Familiarity with explainable AI and rules-based hybrid detection approaches.
Culture & Benefits
- Remote work from the United States.
- Work directly with customers on live accounts within a regional customer team.
- Culture based on mutual trust, support, and professional growth.
- Opportunity to contribute to AML compliance and fraud prevention.
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