Posted:13 hours ago
- Analyzing complex data modeling requirements and translating business questions into analytical solutions
- Developing statistical models, exploratory analyses, and descriptive outputs that support client decision making- Building and refining data pipelines, data quality checks, and scalable modeling workflows- Creating clear visualizations and summaries that communicate findings to technical and nontechnical audiences- Using Python, R, and machine learning tools to support predictive modeling and data science workstreams- Interpreting large data sets to identify patterns, trends, and potential areas for deeper review- Reviewing deliverables for accuracy and alignment with professional and technical standards- Guiding junior team members through assigned tasks and providing feedback on analysis and model development- Adapting approaches to changing client needs, ambiguous problem statements, and shifting project priorities- Applying AI fluency and data science methods to improve model performance and strengthen solution design
- Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering
- Demonstrating data modeling experience within client service engagements- Applying critical thinking to complex data structures and concepts- Interpreting data to inform insights and recommendations- Building meaningful client connections across diverse teams- Mentoring junior team members while managing assigned workstreams
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Hybrid
Full Time
PwC
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