Staff Data Scientist - Fraud & Risk

Glocomms; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Glocomms seeks a Staff Data Scientist to join its Fraud & Risk organization in the United States. You will own end-to-end ML projects from research to deployment, building systems that scale for fraud prevention and identity verification.

You will collaborate with Engineering, Product, and Risk teams, mentor junior teammates, and present insights to technical and executive stakeholders, delivering measurable business impact.

Qualifications

• Master's degree or PhD in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.
• 8+ years of experience in Data Science, ML, AI or related disciplines.
• Proven experience developing, deploying, and maintaining ML models in production.
• Expertise in Python, SQL, and modern ML frameworks including PyTorch, TensorFlow, and scikit-learn.
• Strong understanding of ML algorithms, evaluation methodologies, feature engineering, and data pipeline development.
• Hands-on experience with transformers, graph neural networks, NLP, and computer vision applications.
• Experience working in fast-paced, collaborative environments and driving technically complex projects independently.
• Excellent communication skills to explain complex concepts to technical and non-technical audiences.

Responsibilities

• Design, build, and deploy advanced ML and deep learning models for fraud, risk, and identity challenges.
• Lead development of solutions using transformers, graph learning, CNNs, RNNs, and other AI techniques.
• Own end-to-end model development: data exploration, feature engineering, training, validation, deployment, and monitoring.
• Work with large-scale structured and unstructured data across multiple sources.
• Conduct research to identify new approaches improving model performance and business outcomes.
• Collaborate with Product, Engineering, and Risk teams to translate business challenges into scalable ML solutions.
• Present findings and recommendations to technical and executive stakeholders.
• Mentor junior team members and promote technical excellence.

Skills

Python

SQL

Machine Learning

Deep Learning

Model Deployment

Communication skills

Mentorship

Education

Master's degree / PhD in CS/DS/Statistics

Tools

PyTorch

TensorFlow

scikit-learn

LangChain

Job description

A high-growth technology company is seeking a Staff Data Scientist to join its Fraud & Risk organization. This is an opportunity to work on some of the most challenging machine learning problems in the industry, developing models that drive fraud prevention, risk assessment, and identity intelligence at scale.

This role is ideal for a hands-on data scientist who enjoys owning the full machine learning lifecycle, from research and experimentation through deployment and production monitoring. The successful candidate will partner closely with engineering, product, and business stakeholders to develop innovative solutions that have a direct impact on both customers and the business.

Responsibilities

• Design, build, and deploy advanced machine learning and deep learning models to address fraud, risk, and identity-related challenges.


• Lead the development of solutions leveraging transformers, graph learning algorithms, CNNs, RNNs, and other modern AI techniques.


• Own the end-to-end model development process, including data exploration, feature engineering, training, validation, deployment, and monitoring.


• Work with large-scale structured and unstructured datasets spanning multiple data sources and modalities.


• Conduct research and experimentation to identify new approaches that improve model performance and business outcomes.


• Collaborate with Product, Engineering, and Risk teams to translate business challenges into scalable machine learning solutions.


• Present analytical findings and recommendations to technical and executive stakeholders.


• Mentor junior team members and contribute to a culture of technical excellence and continuous innovation.

Qualifications

• Master's degree, PhD, or equivalent industry experience in Computer Science, Data Science, Statistics, Applied Mathematics, Machine Learning, or a related field.


• 8+ years of experience in Data Science, Machine Learning, Artificial Intelligence, or related disciplines.


• Proven experience developing, deploying, and maintaining machine learning models in production environments.


• Expertise in Python, SQL, and modern machine learning frameworks including PyTorch, TensorFlow, and scikit-learn.


• Strong understanding of machine learning algorithms, model evaluation methodologies, feature engineering, and data pipeline development.


• Hands-on experience developing deep learning models including transformers, graph neural networks, natural language processing models, and computer vision applications.


• Experience working in fast-paced, highly collaborative environments and driving technically complex projects independently.


• Excellent communication skills with the ability to explain sophisticated concepts to both technical and non-technical audiences.

Preferred Experience

• Fraud detection and prevention


• Risk modeling and analytics


• Identity verification


• Financial technology or payments platforms


• Real-time machine learning systems


• Large Language Models (LLMs)


• Agentic AI frameworks


• MLOps and model monitoring


• Graph Neural Networks (GNNs)


• Natural Language Processing (NLP)


• Computer Vision

Key Technologies

Python * SQL * PyTorch * TensorFlow * scikit-learn * Machine Learning * Deep Learning * Transformers * Graph Learning * GNNs * NLP * Computer Vision * LLMs * Agentic AI * LangChain * LangGraph * MLOps * Fraud Detection * Risk Modeling * Identity Intelligence

Please note: Candidates must be authorized to work in the United States without current or future sponsorship requirements.