Applied AI and Data Science Specialist – Global Research Modernization

Join J.P. Morgan’s Global Research Center and help modernize research through applied AI, machine learning and data science, delivering innovative solutions that enhance research methodologies, workflows and outputs. As an Applied AI and Data Science Specialist within the Global Research Modernization team , you will be responsible for developing and implementing AI and data science solutions that enhance research methodologies and outputs. You will translate business problems into deployable data science solutions using Python, machine learning and Large Language Models (LLMs). You will collaborate with research analysts and stakeholders to identify opportunities for data-driven insights and workflow automation. You will support solutions from data exploration and model development through validation and deployment. You will ensure solutions adhere to appropriate data integrity, regulatory and model governance standards. Job Responsibilities Develop applied data science solutions using Python, from problem framing and data exploration through model development, validation and deployment. Implement AI and data science strategies to enhance research methodologies and outputs. Automate workflows for global research teams using AI techniques, including Large Language Models (LLMs). Collaborate with research analysts and stakeholders to identify opportunities for data-driven insights and automation. Ensure the integrity, accuracy and accessibility of data used for analysis and model development. Evaluate emerging AI and data science technologies for potential application within research. Communicate analytical concepts, model outputs and insights effectively to stakeholders. Adhere to regulatory, ethical, data-use and model governance standards. Required Qualifications, Skills and Capabilities 1-5 years of experience working with AI and data science in the financial sector. Strong hands-on knowledge of data science, artificial intelligence and machine learning concepts. Strong proficiency in Python, with hands-on experience using data manipulation libraries including Pandas and NumPy. Knowledge of model development, validation and evaluation techniques. Understanding of supervised and unsupervised learning, deep learning and natural language processing. Demonstrated ability to translate business problems into practical data science solutions. Bachelor’s degree or higher in Engineering, Data Science or a related field. Excellent communication, presentation, interpersonal and organizational skills. Strong attention to detail with a disciplined approach to processes and controls. Preferred Qualifications, Skills and Capabilities Experience applying Large Language Models (LLMs) to research or workflow automation. Experience developing and deploying data science solutions in batch or real-time environments. Knowledge of financial data and financial research methodologies. Experience with feature engineering and production deployment of machine learning models. Familiarity with emerging AI technologies and their application to research workflows.