Data Scientist - Process Intelligence

Join our vibrant Process Intelligence team, where innovation and data science intersect in an exciting, collaborative environment. As a Junior Data Scientist, you'll decode how organizational work truly functions by exploring human-system interactions and leveraging machine learning to advance our industry-leading execution of digital workplace analysis. Our mission is to inspire change and deliver value, fostering a culture of curiosity and deep understanding of process and behavior within systems. By eliminating inefficiencies and unlocking human capital, we empower employees with data-driven insights that guide next-generation workflows. Welcome to Human-in-the-loop 2.0.

As a Junior Data Scientist in our Process Intelligence team, you'll leverage your data science skills to analyze digital trace data and human-system signals. You'll drive innovation and efficiency at JPMorgan Chase through machine learning and data analysis, contributing to the advancement of our digital workplace solutions.

Job Responsibilities:

• Analyze correlations and patterns in telemetry, user activity logs, surveys, and interviews.
• Design and execute experiments to evaluate digital tools and human-system interactions.
• Develop ML models to classify workflows, identify bottlenecks, and predict engagement.
• Construct cognitive and performance metrics from task mining and system logs.
• Collaborate with researchers and engineers to translate workplace signals into business recommendations.
• Create reports and dashboards highlighting system impact and operational insights.

Required Qualifications, Capabilities, and Skills :

• Bachelor's degree in Data Science, Computer Science, Statistics, or a related field.
• 1 or more years of experience in data science or applied research.
• Proficiency in Python, SQL, and data science libraries (e.g., pandas, scikit-learn).
• Strong analytical skills with knowledge of regression analysis.
• Ability to interpret and communicate data-driven insights effectively.
• Effective collaboration skills with diverse stakeholders
• Proficiency in Python for data engineering tasks.

Preferred Qualifications, Capabilities, and Skills:

• Master's degree in Data Science, Computer Science, Statistics, or a related field.
• Exposure to task mining, process mining, or workflow optimization tools.
• Familiarity with psychometrics, cognitive load measurement, or behavioral telemetry.
• Experience with structured and unstructured data analysis.
• Ability to set up and analyze A/B or multivariate experiments.
• Familiarity with data visualization tools (Tableau, PowerBI).
• Experience with cloud-based data tools (Snowflake, Spark, AWS).