Data Scientist II — Fraud & Identity Intelligence

United States Digital Space LLC; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

United States Digital Space LLC is seeking a Data Scientist II to join our Digital Intelligence team. You will develop machine learning features, analytical methods, and risk signals using telemetry from devices, networks, browsers, and mobile platforms.

This hands-on role requires delivering scoped projects, working with noisy data, and partnering with engineering, product, and risk teams to improve fraud detection and identity confidence.

Qualifications

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Data Science, or related field, or equivalent practical experience.
• 5+ years of experience in data science, applied ML, analytics, or related technical role.
• Experience building, evaluating, and improving ML models, features, or risk signals.
• Strong SQL skills and experience with large-scale datasets.
• Proficiency in Python and data science libraries (pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch).
• Experience with distributed data processing tools (Spark, PySpark, Databricks).
• Understanding of supervised/unsupervised learning, feature engineering, model evaluation, and experiment analysis.
• Ability to work with noisy data, imperfect labels, and changing data distributions.
• Strong analytical judgment and ability to communicate with cross-functional teams.

Responsibilities

• Develop machine learning features, models, and analytical methods for device, network, browser, mobile, session, and behavioral intelligence.
• Tackle scoped fraud and identity risk problems with data quality, labels, telemetry coverage, and product tradeoffs.
• Build features from large-scale, high-cardinality telemetry; handle noisy and platform-dependent data.
• Analyze signal patterns like spoofing, emulator behavior, automation, VPN usage, and fingerprinting.
• Design and execute validation analyses: train/test splits, leakage checks, drift assessment, and customer impact analysis.
• Use supervised, unsupervised, statistical, and heuristic approaches to identify durable fraud signals.
• Investigate imperfect labels, instrumentation gaps, and evolving fraud patterns to distinguish useful signal from artifacts.
• Collaborate with engineering, product, risk, and platform teams to prepare data, implement features, and support production rollout.
• Contribute to model documentation, feature definitions, explainability materials, dashboards, and production-readiness reviews.
• Communicate methods, assumptions, findings, limitations, and recommendations to technical and cross-functional stakeholders.
• Support junior data scientists through code review and mentoring.

Skills

Python

SQL

Machine Learning

Pandas

Scikit-learn

Education

Bachelor’s/Master’s/PhD in CS/ML/Statistics

Tools

Spark

Databricks

TensorFlow

PyTorch

Job description

United States Digital Space LLC is seeking a Data Scientist II to join our Digital Intelligence team. You will develop machine learning features, analytical methods, and risk signals using telemetry from devices, networks, browsers, and mobile platforms.

This hands-on role requires delivering scoped projects, working with noisy data, and partnering with engineering, product, and risk teams to improve fraud detection and identity confidence.