Top AI & Machine Learning Jobs

Lead and execute compliance assessments of scripts and models (CoDIR), identify high-risk scripts, prepare and report findings, monitor governance inventory, and explore GenAI/automation to improve processes.

Lead development and evaluation of statistical and machine learning models to assess credit risk and challenge production models. Use Python, cloud, and big-data tools to analyze large numeric and textual datasets, partner with cross-functional credit risk and product teams, translate technical findings into business actions, and drive model validation, backtesting, and innovation.

Build, validate, and deploy machine learning models across the credit card lifecycle using big data tools. Partner with cross-functional teams to turn insights from large numeric and textual datasets into business impact.

Lead development and deployment of machine learning models across the credit card lifecycle. Partner with cross-functional teams to build data-driven products, analyze large numeric and textual datasets, validate and implement models, and translate technical insights into business impact.

The Data Scientist will innovate using ML technologies to analyze data, build models, and create scalable solutions while collaborating with cross-functional teams.

The role involves partnering with data scientists and engineers to develop machine learning models, evaluate model risk in fraud detection, and translate complex data insights into business goals.

The Data Scientist Manager leads a team in assessing model risks, developing machine learning models, and presenting insights, while leveraging various technologies.

The role involves leading AI research projects, building AI foundation models, collaborating with engineering teams, and mentoring applied scientists to enhance customer interactions through AI.

Lead production of machine learning applications, provide technical expertise, and mentor engineers to drive ML model delivery at scale.

The role involves leading a team to develop machine learning models for personalized customer experiences, leveraging large datasets and advanced techniques, while collaborating with cross-functional teams.