Data Scientist – Network Intelligence & Fraud Analytics

Title – Data Scientist – Network Intelligence & Fraud Analytics

Location: Remote with frequent travel to Seattle, WA.

Type: FTE/Contract

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

Required Qualifications

• 15+ 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

Preferred

• 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)