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Senior Data Scientist, Model Risk & Data Analytics, Internal Audit - AMS

New York, United States of America💼 Full-time🗓 2026-09-28

Core

Build state-of-the-art analytics products and AI/ML models to enable continuous auditing, risk identification, and model risk management within the Internal Audit function.

Role type

Senior IC data scientist (model risk & audit)

Builds

Proprietary ML/AI models, data warehouses, ETL pipelines, and self-service analytics dashboards for audit teams

Domain

Financial services / Internal Audit / AI & Machine Learning

Deliverable

production ML models

Required skills

LLM auditing frameworks, model lifecycle risk assessment, bias/fairness quantification, hallucination rate measurement, transformer architecture expertise, SQL, Python (PyTorch, TensorFlow, scikit-learn), ML pipeline orchestration

Preferred skills

PhD in quantitative discipline, LLM Auditor methodology familiarity, data integration/ETL design, cloud infrastructure (AWS/GCP/Azure/Snowflake), large-scale data processing (Hadoop/Flink/MapReduce), front-end/back-end development

Technologies

Hugging Face Transformers, TensorFlow, PyTorch, scikit-learn, AWS, GCP, Azure, Snowflake, Hadoop, Flink, MapReduce

Responsibilities

Conduct audits on the model lifecycle ensuring compliance with quality and risk standards; Identify model vulnerabilities including bias, fairness violations, and security risks; Define and assess model performance metrics and stability analyses; Develop data warehouses and ETL pipelines to support audit engagements; Leverage ML/AI to automate business and audit processes; Provide data training to empower the audit team

Seniority

Senior, hands-on IC

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