Data Scientist II - Real-Time Fraud & Identity Intelligence

Careers; New York (NY); Sur place; USD 120 000 - 155 000; Plein temps

Résumé du poste

Careers is partnering with a high-growth leader in digital identity, fraud prevention, and risk intelligence to join their Digital Intelligence team as a Data Scientist II. You will build features, models, and signals powering real-time fraud detection and identity decisions at scale.

You will work with huge telemetry datasets to uncover patterns, develop production-grade signals, and contribute to model explainability and dashboards across a sophisticated ML platform.

Qualifications

• 5+ years of experience in Data Science, ML, or analytics engineering.
• Strong Python and SQL skills with production ML experience.
• Experience building models, features, and data pipelines.

Responsabilités

• Build machine learning features, models, and analytical methods for fraud detection and identity verification.
• Analyze large-scale, high-cardinality datasets to identify predictive signals.
• Investigate fraud patterns including automation, spoofing, and device fingerprinting.
• Design and execute model validation strategies: holdout testing, drift detection, leakage reviews, stability assessments.
• Collaborate with Engineering, Product, Analytics, and Risk to productionize DS initiatives.
• Contribute to model explainability, documentation, dashboards, and production-readiness reviews.
• Communicate findings to both technical and non-technical stakeholders.

Connaissances

Python

SQL

Machine Learning

Feature Engineering

Model Evaluation

Distributed Computing

Outils

Pandas

NumPy

Scikit-learn

XGBoost

TensorFlow

PyTorch

Spark

PySpark

Databricks

Description du poste

Careers is partnering with a high-growth leader in digital identity, fraud prevention, and risk intelligence to join their Digital Intelligence team as a Data Scientist II. You will build features, models, and signals powering real-time fraud detection and identity decisions at scale.

You will work with huge telemetry datasets to uncover patterns, develop production-grade signals, and contribute to model explainability and dashboards across a sophisticated ML platform.