Data Scientist II - Digital Intelligence

Glocomms; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Glocomms is seeking a Data Scientist II in New York to build machine learning features and risk signals for real-time fraud detection. You will work with Engineering, Product, Analytics, and Risk to deploy models into production and contribute to explainability and dashboards.

The role emphasizes production-ready ML systems, scalable data pipelines, and collaboration with cross-functional teams to advance digital trust at scale.

Qualifications

• 5+ years in Data Science or related field.
• Strong Python with listed libraries.
• Advanced SQL with large datasets.
• Experience building ML models and pipelines.
• Understanding of supervised/unsupervised learning.
• Experience with distributed processing tools.

Responsibilities

• Build ML features, models, and risk-focused analytics.
• Analyze large-scale, noisy datasets for signals.
• Investigate fraud behaviors like spoofing and VPN usage.
• Design model validation strategies including drift and leakage checks.
• Collaborate with Engineering, Product, Analytics, and Risk to productionize.
• Document features, dashboards, and production-readiness reviews.
• Present findings to technical and non-technical stakeholders.

Skills

Python

Pandas

NumPy

Scikit-learn

XGBoost

TensorFlow

PyTorch

SQL

Data analysis

Spark

Databricks

Tools

Databricks

PySpark

Job description

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.