GCP Architect
Columbus, IN · On-site
$59.25 - $76.25/hr
... AML, KYC, Regulatory Compliance, Data Compliance, Operationalizing AI/ML Models, Cross-Functional Collaboration, Data Science, Risk Analytics, Enterprise Solutions
GCP Architect
Columbus, IN · On-site
$59.25 - $76.25/hr
... AML, KYC, Regulatory Compliance, Data Compliance, Operationalizing AI/ML Models, Cross-Functional Collaboration, Data Science, Risk Analytics, Enterprise Solutions
Bachelor's degree, or equivalent experience, in Computer Science, Data Science, Engineering, or a ... Experience supporting anti-money laundering (AML), fraud, financial crime, investigations, or ...
Bachelor's degree, or equivalent experience, in Computer Science, Data Science, Engineering, or a ... Experience supporting anti-money laundering (AML), fraud, financial crime, investigations, or ...
Aml Data Scientist information
What is the difference between Aml Data Scientist vs Fraud Data Analyst?
| Aspect | Aml Data Scientist | Fraud Data Analyst |
|---|---|---|
| Required Credentials | Data science degree, knowledge of AML regulations, data analysis skills | Data analysis background, understanding of fraud detection methods |
| Work Environment | Financial institutions, compliance teams, AML departments | Banking, insurance, or e-commerce sectors focusing on fraud prevention |
| Employer & Industry Usage | Used in banking, finance, and AML compliance | Common 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 skills and qualifications are needed to thrive as an AML data scientist?
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.
What are popular job titles related to Aml Data Scientist jobs in Indiana?
For Aml Data Scientist jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Aml Data Scientist jobs in Indiana look for?
The top searched job categories for Aml Data Scientist jobs in Indiana are:
$59.25 - $76.25/hr
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Job description
Data Engineering & Modeling
Data Modeling, Logical Data Modeling, Physical Data Modeling, Dimensional Data Modeling, Data Vault Modeling, Data Engineering, Enterprise Data Models, Data Pipelines, Data Governance, Data Architecture, Data Mesh, Lakehouse Architecture
Real-Time Data Processing
Real-Time Data Pipelines, Streaming Data Processing, Event-Driven Architecture, Apache Kafka, Google Pub/Sub, Low-Latency Data Processing
Google Cloud Platform (GCP)
Google Cloud Platform, BigQuery, Dataflow, Pub/Sub, Vertex AI, Cloud Architecture, GCP Professional Data Engineer, GCP Professional Cloud Architect
AI, Machine Learning & MLOps
Machine Learning, AI/ML Model Deployment, ML Inferencing, MLOps, Model Monitoring, Model Governance, Model Risk Management, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vector Databases, MLflow, Kubeflow
Cloud & Data Technologies
Python, SQL, API Integration, Kubernetes, Docker, CI/CD, Apache Spark, Databricks, Snowflake
Banking & Financial Domain
Banking, Fraud Detection, Risk Management, AML, KYC, Regulatory Compliance, Data Compliance, Operationalizing AI/ML Models, Cross-Functional Collaboration, Data Science, Risk Analytics, Enterprise Solutions
Data Modeling, Logical Data Modeling, Physical Data Modeling, Dimensional Data Modeling, Data Vault Modeling, Data Engineering, Enterprise Data Models, Data Pipelines, Data Governance, Data Architecture, Data Mesh, Lakehouse Architecture
Real-Time Data Processing
Real-Time Data Pipelines, Streaming Data Processing, Event-Driven Architecture, Apache Kafka, Google Pub/Sub, Low-Latency Data Processing
Google Cloud Platform (GCP)
Google Cloud Platform, BigQuery, Dataflow, Pub/Sub, Vertex AI, Cloud Architecture, GCP Professional Data Engineer, GCP Professional Cloud Architect
AI, Machine Learning & MLOps
Machine Learning, AI/ML Model Deployment, ML Inferencing, MLOps, Model Monitoring, Model Governance, Model Risk Management, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vector Databases, MLflow, Kubeflow
Cloud & Data Technologies
Python, SQL, API Integration, Kubernetes, Docker, CI/CD, Apache Spark, Databricks, Snowflake
Banking & Financial Domain
Banking, Fraud Detection, Risk Management, AML, KYC, Regulatory Compliance, Data Compliance, Operationalizing AI/ML Models, Cross-Functional Collaboration, Data Science, Risk Analytics, Enterprise Solutions
About Virtusa
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We are builders, makers, and doers with the technical skills and domain expertise to transform your business at scale and speed without disruption. Our unique Engineering First approach blends deep industry expertise and empowered, agile teams, to create holistic solutions that seamlessly move the business forward. We help clients engage with new technology paradigms to creatively build solutions that drive them to the forefront of their industries.
Industry
It services
Company size
10,000+ Employees
Headquarters location
Westborough, MA, US
Year founded
1996