Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Build and integrate fraud detection machine learning models for banking transaction analysis, with a strong focus on graph-based methods to uncover complex relationships such as cryptocurrency flows. Research and apply state-of-the-art approaches for anomaly detection in AML data, implement production-ready code primarily in Python, and collaborate on GraphRAG components for AI-driven agents. Document and present research findings to support continuous improvements to the Fraud Protection platform.

Location: Tashkent

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Identify and formalize fraud/AML scenarios covered by the transactional antifraud system.
•Research and evaluate ML models and techniques for fraud and anomaly detection in transactional data.
•Build classic, graph-based, and neural network ML models and integrate them into the Fraud Protection platform.
•Develop production-ready source code primarily in Python (Go experience is a plus).
•Document and present research findings.

Pay and Benefits

Perks:Health Insurance

Key Requirements

•Solid foundation in transactional data analysis for fraud detection and anomaly detection.
•Understanding of classical ML and neural networks, especially Graph ML (node embeddings, link prediction, GNNs).
•Hands-on experience with PyTorch or Keras/TensorFlow.
•Experience designing and building ETL pipelines.
•Ability to develop in both IDE-based and terminal-based workflows.

Skills:DocumentationPresentationExperimentationResearch mindset

Certifications:CEHCISSPOSCPGIACMCFEBSI

Tech Stack:Python 3.8+PandasScikit-learnPyTorchNetworkXPyGNeo4jAWS NeptuneElasticsearchCassandraClickHouseGitDockerAWS ecosystemGraphRAGKerasTensorFlow

Company Brief

Group IB

Website

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Group IB

8 months ago

Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Tashkent

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Identify and formalize fraud/AML scenarios covered by the transactional antifraud system.
•Research and evaluate ML models and techniques for fraud and anomaly detection in transactional data.
•Build classic, graph-based, and neural network ML models and integrate them into the Fraud Protection platform.
•Develop production-ready source code primarily in Python (Go experience is a plus).
•Document and present research findings.

Pay and Benefits

Perks:Health Insurance

Key Requirements

•Solid foundation in transactional data analysis for fraud detection and anomaly detection.
•Understanding of classical ML and neural networks, especially Graph ML (node embeddings, link prediction, GNNs).
•Hands-on experience with PyTorch or Keras/TensorFlow.
•Experience designing and building ETL pipelines.
•Ability to develop in both IDE-based and terminal-based workflows.

Skills:DocumentationPresentationExperimentationResearch mindset

Certifications:CEHCISSPOSCPGIACMCFEBSI

Tech Stack:Python 3.8+PandasScikit-learnPyTorchNetworkXPyGNeo4jAWS NeptuneElasticsearchCassandraClickHouseGitDockerAWS ecosystemGraphRAGKerasTensorFlow

Company Brief

Group IB

Website