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HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for Data Scientist Network Intelligence & Fraud Analytics in Seattle, WA. Below is the detailed job description.
Title Data Scientist Network Intelligence & Fraud Analytics
Location Seattle, WA (Onsite/Hybrid)
Job Description:
We are hiring Data Scientists with strong telecom/network data expertise to build machine learning models for fraud detection using large-scale telecom signals.
Key Responsibilities
HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for Data Scientist Network Intelligence & Fraud Analytics in Seattle, WA. Below is the detailed job description.
Title Data Scientist Network Intelligence & Fraud Analytics
Location Seattle, WA (Onsite/Hybrid)
Job Description:
We are hiring Data Scientists with strong telecom/network data expertise to build machine learning models for fraud detection using large-scale telecom signals.
Key Responsibilities
- Develop ML models for fraud detection using telecom financial datasets
- Engineer features from CDRs, network events, device fingerprints, geolocation data
- Build real-time and batch fraud scoring pipelines
- Implement anomaly detection, graph analytics, and behavioral modeling techniques
- Work with streaming platforms (Kafka) and large-scale data processing (Spark)
- Collaborate with SMEs to incorporate domain-driven features and rules
- Evaluate models using fraud-specific metrics (AUC, precision-recall, lift, cost savings)
- Optimize models for low latency and high scalability in production environments
- 5 10 years in Data Science / ML with strong telecom/network data experience
- Expertise in Python, ML frameworks (scikit-learn, PyTorch, etc.)
- Experience with big data tools (Spark, Hadoop) and streaming (Kafka)
- Strong understanding of network data structures (CDR, signaling, device data)
- Experience building fraud/anomaly detection models
- Experience with graph-based fraud detection (network/relationship analysis)
- Exposure to real-time ML deployment (MLOps, APIs, Kubernetes)
- Background in both telecom and financial datasets (highly desirable)