Job Description

The Private Bank Client Service Analytics Team at J.P. Morgan is dedicated to enhancing the client experience by leveraging advanced data analytics and machine learning techniques. Our team supports the U.S. Private Bank by providing actionable insights and data-driven solutions to improve client relationships and service delivery. We are looking for a passionate and innovative Data Scientist to join our team and help us drive excellence in client service through data analytics.

Job Responsibilities:

• Client Insights Analysis: Leverage data from internal and external sources, including customer surveys, complaints, and feedback, to identify key opportunities for improving the client experience.
• Collaborate with Stakeholders: Work closely with business partners, technologists, product managers, and control partners to deploy data-driven solutions into production and ensure alignment with business goals.
• Reporting and Visualization: Prepare and distribute comprehensive reports and visualizations that summarize key insights and trends to senior leadership, providing clear and actionable recommendations.
• Develop Advanced Analytics Solutions: Research, develop, and implement machine learning models to solve real-world problems related to client service, including natural language processing (NLP), speech analytics, and time-series predictions.
• Drive Continuous Improvement: Identify and implement process improvements to enhance the efficiency and effectiveness of client service operations, leveraging data to drive decision-making.
• Knowledge Sharing: Participate in the knowledge-sharing community by staying up-to-date with the latest advancements in machine learning and data analytics, and sharing insights with the team.

• Educational Background: PhD or MS in a quantitative discipline such as Computer Science, Data Science, Mathematics, Statistics, or a related field with significant industry or research experience.
• Technical Expertise: Strong background in machine learning and deep learning methods, with hands-on experience using toolkits such as TensorFlow, PyTorch, NumPy, Scikit-Learn, and Pandas.
• Analytical Skills: Excellent quantitative and analytical problem-solving skills, with the ability to synthesize and interpret complex data from various sources.
• Communication Skills: Strong written and verbal communication skills, with the ability to effectively communicate technical concepts and results to both technical and business audiences.
• Collaboration: Proven ability to work in a highly collaborative environment, with excellent stakeholder management skills and the ability to influence and drive accountability.
• Project Management: Ability to manage multiple concurrent projects, prioritize tasks, and deliver results in a fast-paced environment.
• Advanced Tools: Proficiency in SQL and experience with large data sets, as well as advanced Excel and PowerPoint skills for creating compelling presentations.
• Platform Knowledge: Experience with Snowflake and Databricks platforms.
• Visualization Tools: Knowledge of QlikView is beneficial, but Tableau is preferred.
• Data Preparation Tools: Experience with Alteryx.
• Programming Skills: Proficiency in Python is mandatory, with 3-5 years of experience and the ability to function daily in Python.
• LLM Expertise: Understanding of Large Language Models (LLMs) and the ability to use LLMs for coding and NLP tasks.