Key skills
CloudNeo4jPythonPyTorchScikit-LearnSQLAIMachine LearningMLGenerative AILarge Language ModelsRAGscikit-learnHugging FaceAnalyticsCosmos DB
About this role
Role Overview
- Lead end to end development of fraud detection and risk analytics models
- Perform advanced modeling and AI analysis on large, complex datasets to identify emerging fraud patterns
- Demonstrate proficiency in developing, fine-tuning, and deploying Generative AI models such as GPT models
- Build and optimize modular RAG (Retrieval-Augmented Generation) systems while managing cloud-based solutions
- Apply large language models (LLMs) to parse complex documents and extract structured information
- Collaborate with data engineers and ML engineers to integrate data science solutions into existing systems
- Communicate sophisticated technical concepts to both technical and non-technical partners
Requirements
- Master’s or Ph.D. degree in Computer Science, Data Science, Statistics, Engineering, Physics, or a related quantitative field
- 5+ years of hands-on industry experience in developing probabilistic models, analytics, and machine learning algorithms
- Proficiency in programming languages such as Python and experience with machine learning libraries/frameworks, e.g., PyTorch, scikit-learn, Hugging Face, SQL, graph databases (Neo4j/Cypher, Cosmos DB)
Tech Stack
- Cloud
- Neo4j
- Python
- PyTorch
- Scikit-Learn
- SQL
Benefits
- Health insurance
- Dental insurance
- Mental health benefits
- Vision insurance
- Short
- and long-term disability insurance
- Life and AD&D insurance coverage
- Adoption/surrogacy benefits
- Wellness benefits
- Employee/family assistance plans
- Retirement savings plans (including pension/401(k) savings plans and a global share ownership plan with employer matching contributions)
- Financial education and counseling resources
- Paid time off including up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time