1

Aml Data Scientist Jobs (NOW HIRING)

Data Scientist Location: Boston, Ma Duration: 12++ Months Position description and responsibilities ... R, Matlab, AML etc.) Bring not just an analytics-orientation, but the ability to use analytics to ...

... KYC/AML data. • Experience with Databricks-native AI/ML tooling: Databricks Vector Search ... Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent ...

... problems (AML, fraud detection, mortgage default, foreclosure, credit risk management, price ... • Data Science Languages - SAS, SAS Enterprise Miner, R Programming, Python, Spark • ...

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

Data Scientist III - FCRM

Portland, ME · On-site

$96K - $155K/yr

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

Data Scientist III - FCRM

Boston, MA · On-site

$96K - $155K/yr

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

Data Scientist III - FCRM

New York, NY · On-site

$96K - $155K/yr

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

Data Scientist III - FCRM

Vienna, VA · On-site

$96K - $155K/yr

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

Data Scientist III - FCRM

Greenville, SC · On-site

$96K - $155K/yr

AML, Financial Crime, Compliance, Audit, Risk, or Transaction Monitoring experience. * Experience ... data science * Is familiar with the business context and data infrastructure and can translate ...

New

next page

Showing results 1-20

Aml Data Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do aml data scientist jobs pay per year?

As of Jul 26, 2026, the average yearly pay for aml data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Aml Data Scientist vs Fraud Data Analyst?

AspectAml Data ScientistFraud Data Analyst
Required CredentialsData science degree, knowledge of AML regulations, data analysis skillsData analysis background, understanding of fraud detection methods
Work EnvironmentFinancial institutions, compliance teams, AML departmentsBanking, insurance, or e-commerce sectors focusing on fraud prevention
Employer & Industry UsageUsed in banking, finance, and AML complianceCommon in banking, retail, and online services for fraud detection

While both roles involve data analysis within financial services, an Aml Data Scientist specializes in anti-money laundering efforts, utilizing advanced analytics and machine learning. A Fraud Data Analyst focuses on detecting and preventing various types of fraud, often using similar data tools but with a different focus area. Both roles require strong analytical skills and familiarity with industry regulations, but their primary objectives and specific expertise differ.

How does an AML Data Scientist typically collaborate with compliance and engineering teams to enhance anti-money laundering efforts?

An AML Data Scientist frequently works alongside compliance officers to understand regulatory requirements and suspicious activity patterns, translating these into data-driven models and analytics. They also partner with engineering teams to integrate machine learning solutions into existing transaction monitoring systems, ensuring data pipelines are robust and scalable. Regular cross-functional meetings and project updates are common, fostering a collaborative environment where technical and regulatory expertise combine to strengthen anti-money laundering strategies.

What is an AML Data Scientist?

An AML Data Scientist is a professional who uses data analysis, machine learning, and statistical techniques to detect and prevent money laundering activities within financial institutions. They analyze large volumes of transactional and customer data to identify suspicious patterns and support compliance with anti-money laundering (AML) regulations. Their work helps organizations meet regulatory requirements and reduce financial crime risks through advanced analytics and predictive modeling.

What are the key skills and qualifications needed to thrive as an AML Data Scientist, and why are they important?

To thrive as an AML Data Scientist, you need a solid background in statistics, data analysis, and machine learning, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with anti-money laundering (AML) regulations, SQL, Python, and analytics platforms like SAS or Spark, as well as knowledge of relevant certifications (e.g., CAMS), is essential. Strong problem-solving abilities, analytical thinking, and effective communication skills help you interpret complex data and collaborate with compliance teams. These skills ensure accurate detection of suspicious activities, regulatory compliance, and effective risk management within financial institutions.
More about Aml Data Scientist jobs
What cities are hiring for Aml Data Scientist jobs? Cities with the most Aml Data Scientist job openings:
What states have the most Aml Data Scientist jobs? States with the most job openings for Aml Data Scientist jobs include:
Infographic showing various Aml Data Scientist job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 9% Internship, 53% As Needed, 33% Full Time, 3% Part Time, and 1% Contract. Highlights an 84% Physical, 7% Hybrid, and 9% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Data Scientist, AI Data Foundations

Data Scientist, AI Data Foundations

NextDeavor Inc.

Irvine, CA • Remote

$114K - $175K/yr

Contractor

Posted 23 days ago


Job description

Data Scientist, AI Data Foundations
Full-time
Remote
Exclusive confidential search — details shared with qualified applicants.
 
Become a Key Player as a Data Scientist, AI Data Foundations

You will design and build the curated data structures that AI and ML applications consume, enabling higher-quality model training and inference. You will partner with model builders, product, risk, and growth stakeholders to surface actionable insights and ship production-ready vector, feature, and graph data assets. This is a Remote role.

Here's How You'll Make an Impact on the Team
  • Build and maintain vector stores for RAG, including embedding pipelines, chunking strategies, indexing, and refresh patterns.
  • Own the feature store: design, build, and operate feature definitions, freshness SLAs, lineage, and point-in-time correctness for offline/online use.
  • Design and implement graph data structures to model relationships across applicants, applications, products, lenders, decisions, and outcomes.
  • Lead data discovery: profile lending, deposit, and behavioral datasets to identify trends, segments, anomalies, and model drivers; produce actionable hypotheses for stakeholders.
  • Engineer curated, AI-ready datasets with appropriate quality checks, documentation, and governance for downstream model builders and analysts.
  • Define and run evaluation frameworks for RAG retrieval quality, feature drift, embedding quality, and graph completeness; iterate on metrics.
  • Partner closely with ML engineers and applied scientists to ensure data assets accelerate model development and serving workflows.
  • Champion responsible data use by collaborating with governance, security, and compliance teams to ensure data classification, consent, and regulatory boundaries are respected.
  • Communicate findings via write-ups, notebooks, dashboards, and short presentations for technical and non-technical audiences.
Here's What You'll Need to Be Successful in This Role
  • 4–7 years of experience in data science, ML engineering, or applied data roles, with significant time building data assets consumed by models or applications.
  • Hands-on experience designing and operating vector stores for RAG or semantic search (embedding generation, chunking, indexing, retrieval evaluation).
  • Experience building or operating a feature store (e.g., Databricks Feature Store, Feast, or custom), including offline training and online serving patterns and point-in-time correctness.
  • Experience modeling and building graph data structures and writing graph queries (Neo4j, TigerGraph, Cosmos DB Gremlin, or similar).
  • Strong proficiency in Python (pandas, NumPy, scikit-learn, PySpark) and SQL; comfortable using Databricks notebooks and jobs.
  • Practical experience with embedding models and LLM tooling (Hugging Face, OpenAI/Azure OpenAI APIs, LangChain or similar) in production or near-production contexts.
  • Demonstrated data discovery skills: profiling messy datasets, surfacing patterns, validating findings statistically, and explaining results clearly.
  • Solid grounding in classical ML concepts (supervised vs. unsupervised learning, train/test discipline, leakage, evaluation metrics).
  • Strong written and verbal communication skills for technical and business audiences.
Here's What Else Might Help You Out
  • Experience in SaaS or FinTech, especially with lending, deposit, credit, fraud, or KYC/AML data.
  • Familiarity with Databricks-native AI/ML tooling: Databricks Vector Search, Databricks Feature Store, MLflow, Unity Catalog.
  • Experience with open-source vector DBs (pgvector, Pinecone, Weaviate, Chroma, FAISS) and strong opinions on trade-offs.
  • Experience with Microsoft Azure data and AI services (Azure OpenAI, Azure AI Search, ADLS Gen2).
  • Experience evaluating RAG systems end-to-end (recall@k, faithfulness, answer quality, hallucination measurement).
  • Exposure to graph algorithms (community detection, link prediction, centrality) applied to business problems.
  • Bachelor's or Master's in CS, Statistics, Mathematics, Engineering, or related quantitative field, or equivalent experience.
Pay Range

$114,000 - $175,000/year

Ready to Make Your Mark?

This role may fill quickly. Submit your resume to be considered.

Apply with Pioneers here