What You'll Be Doing
- Build machine learning features, models, and analytical methods focused on fraud detection, identity verification, and risk intelligence.
- Analyze large-scale, high-cardinality, sparse, and noisy datasets to identify meaningful patterns and predictive signals.
- Investigate sophisticated fraud behaviors including automation, spoofing, emulators, VPN/proxy usage, low-entropy fingerprints, and telemetry anomalies.
- Design and execute model validation strategies including holdout testing, drift detection, leakage reviews, stability assessments, and customer impact analysis.
- Partner closely with Engineering, Product, Analytics, and Risk teams to move data science initiatives into production.
- Contribute to model explainability, feature documentation, dashboards, and production-readiness reviews.
- Communicate findings and recommendations to both technical and non-technical stakeholders.
What We're Looking For
- 5+ years of experience in Data Science, Machine Learning, Statistical Modeling, Analytics Engineering, or a related field.
- Strong Python skills with experience using libraries such as Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, PyTorch, or similar.
- Advanced SQL skills and experience working with large, complex datasets.
- Experience developing machine learning models, predictive features, and analytical pipelines.
- Strong understanding of supervised and unsupervised learning, feature engineering, model evaluation, and statistical analysis.
- Experience with distributed data processing tools such as Spark, PySpark, or Databricks.
- Ability to work independently while collaborating across cross-functional teams.
Preferred Experience
- Fraud detection, cybersecurity, identity verification, trust & safety, anomaly detection, or risk modeling.
- Production ML systems, model monitoring, and real-time or near real-time decisioning environments.
- Experience working with adversarial datasets and evolving fraud patterns.
Why Join?
- Work on highly impactful, real-world machine learning challenges.
- Help build systems that prevent fraud and improve digital trust at scale.
- Collaborate with experienced data scientists, engineers, and product leaders.
- Gain deep expertise in digital intelligence, behavioral analytics, and identity risk modeling.
- Opportunity to grow into a senior-level technical contributor while working on production ML systems used by leading organizations.
We're partnering with a high-growth leader in digital identity, fraud prevention, and risk intelligence that is transforming how organizations establish trust online. They are looking for a Data Scientist II to join their Digital Intelligence team and help build the machine learning models, features, and risk signals that power real-time fraud detection and identity decisions at scale.
Interested in learning more? Reach out directly for a confidential conversation.
#J-18808-LjbffrData Scientist II - Digital Intelligence in new york at Unknown Company
This position is listed as full time and onsite.