Applied AI ML Senior Associate - Machine Learning Scientist | London, United Kingdom | JPMorgan Chase & Co.

Position:	Applied AI ML Senior Associate - Machine Learning Scientist
Institution:	JPMorgan Chase & Co.
Location:	London, United Kingdom
Duties:	Research and explore new machine learning methods through independent study, attending industry-leading conferences and experimentation; Develop state-of-the art machine learning models to solve real-world problems and apply it to complex business critical problems in Cybersecurity, Software and Technology Infrastructure; Collaborate with multiple partner teams in Cybersecurity, Software and Technology Infrastructure to deploy solutions into production; Drive firmwide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
Requirements:	PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science. Or an MS with full time industry or research experience in the field; Hands-on experience and solid understanding of machine learning and deep learning methods; Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas); Scientific thinking and the ability to invent

Text:	Applied AI ML Senior Associate - Machine Learning Scientist Research and explore new machine learning methods through independent study, attending industry-leading conferences and experimentation; Develop state-of-the art machine learning models to solve real-world problems and apply it to complex business critical problems in Cybersecurity, Software and Technology Infrastructure; Collaborate with multiple partner teams in Cybersecurity, Software and Technology Infrastructure to deploy solutions into production; Drive firmwide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science. Or an MS with full time industry or research experience in the field; Hands-on experience and solid understanding of machine learning and deep learning methods; Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas); Scientific thinking and the ability to invent