Data Scientist Lead Branch Channel Analytics

We have an exciting opportunity for you to enhance your career in Branch Channel Analytics contributing to innovative banking solutions.

As a Data Scientist Lead at JPMorgan Chase within the Data and Analytics team you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure stable and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firms business objective

Job Responsibilities:

• Serve as the subject matter expert on machine learning techniques and optimizations to drive sales enablement and performance analytics for Chases branch network.
• Design develop and enhance ML workflows to support sales strategies customer segmentation campaign effectiveness and branch performance optimization.
• Conduct experiments using advanced ML and statistical methods analyze results and tune models to deliver actionable insights for sales and customer engagement.
• Actively engage in hands-on coding converting experimental results into robust scalable production solutions.
• Take full ownership of the code development lifecycle in Python from proof of concept and experimentation to production-ready solutions.
• Collaborate with business partners product managers and technology teams to integrate ML solutions into branch operations and sales processes.

Required Qualifications Capabilities and Skills

• Masters in Computer Science Statistics Mathematics Data Science or a related field with at least 8 years of applied data science and machine learning experience.
• Hands on experience in one or more programming languages such as Python R or Java. Intermediate to advanced Python proficiency is required.
• Proven experience applying machine learning techniques to solve business problems in sales analytics customer analytics or financial services.
• Strong background in statistical modeling data mining and machine learning methods (e.g. regression classification clustering time series analysis ensemble methods).
• Experience with machine learning and deep learning frameworks such as scikit-learn PyTorch or TensorFlow.
• Ability to independently manage tasks and projects through to completion with limited supervision.
• Excellent communication skills with the ability to present complex ML concepts to non-technical stakeholders.
• Strong attention to detail and a collaborative team-oriented mindset.

Preferred Qualifications Capabilities and Skills

• Experience in sales enablement analytics marketing analytics or branch/channel performance analytics within banking or financial services.
• In-depth understanding of advanced ML methodologies such as customer segmentation campaign attribution recommender systems uplift modeling and graph analytics.
• Experience with cloud platforms (e.g. AWS Azure GCP) and tools for building and deploying ML models (e.g. Sagemaker Databricks MLflow).
• Familiarity with big data technologies (e.g. Spark Hadoop) and data engineering best practices.
• Software development experience is a plus.