Data Scientist III- Operations

Experteer Overview In this role you will apply optimization and predictive modeling to improve field operations and capacity planning. You will work with senior data scientists and operational stakeholders to build automated workflows and decision-support tools. The role sits on the Operations Data Science & AI team and contributes to scalable analytics that inform routing, scheduling, and resource allocation. You will translate complex problems into actionable models and communicate results clearly. This opportunity lets you shape data-driven operations at scale and collaborate across the organization. Compensation / Benefits * Develop optimization solutions for capacity planning, routing, scheduling, and resource allocation * Formulate business problems using decision variables, objectives, and constraints * Build, test, and maintain forecasting, regression, classification, and anomaly-detection models * Create reproducible data pipelines and automate recurring analyses and model runs * Maintain Snowflake data models and create dashboards for decision support * Document methodologies and present findings to stakeholders Tasks * Hands-on mathematical optimization using MILP formulations * Experience with optimization libraries such as Gurobi, Pyomo, OR-Tools, PuLP, or CPLEX * Strong SQL on Snowflake and Python for analysis * Experience building, testing, and validating predictive models (forecasting, regression, classification) * Workflow automation and reproducible data pipelines * Data visualization and clear communication of results * Ability to turn ambiguous operational problems into analytical solutions Key requirements *

_ * Maintain Snowflake data models and create dashboards for decision support * Document methodologies and present findings to stakeholders Tasks * Hands-on mathematical optimization using MILP formulations * Experience with optimization libraries such as Gurobi, Pyomo, OR-Tools, PuLP, or CPLEX * Strong SQL on Snowflake and Python for analysis * Experience building, testing, and validating predictive models (forecasting, regression, classification) * Workflow automation and reproducible data pipelines * Data visualization and clear communication of results * Ability to turn ambiguous operational problems into analytical solutions Key requirements *