Senior Data Scientist - Operations Optimization

PODS; Clearwater (FL); On-site; USD 110,000 - 150,000; Full time

Job summary

PODS is seeking a Data Scientist to join the Operations Data Science & AI team. You will report to the Director and collaborate with engineers and operational stakeholders to develop optimization and predictive models, and automated workflows that support capacity planning, routing, scheduling, and resource allocation.

Your work will turn data-driven insights into scalable decision-support tools, dashboards, and well-documented methodologies that enhance field operations.

Qualifications

• Bachelor’s degree in a quantitative field; master’s preferred.
• 3+ years of applied data science, ML, or quantitative analytics experience.
• Hands-on experience with SQL on a modern cloud data warehouse (Snowflake preferred) and Python for analysis.
• Experience or coursework in ML and mathematical optimization, with exposure to Snowflake or AWS.

Responsibilities

• Develop optimization solutions: build models for capacity planning, routing, scheduling, and resource allocation.
• Develop predictive models: forecast, regression, classification, and anomaly-detection models; validate results.
• Build and automate workflows: reproducible data pipelines and automated analyses and model runs.
• Develop analytical assets and data models: maintain Snowflake data models and create dashboards.
• Document and communicate clearly: explain methods and results; document logic and assumptions.

Skills

Mathematical optimization

SQL and Python fluency

Applied machine learning

Workflow automation

Data visualization

Communication and documentation

Structure amid ambiguity

Education

Bachelor's degree in quantitative field

Master's degree preferred

Tools

Gurobi

Pyomo

OR-Tools

PuLP

CPLEX

Snowflake

Job description

PODS is seeking a Data Scientist to join the Operations Data Science & AI team. You will report to the Director and collaborate with engineers and operational stakeholders to develop optimization and predictive models, and automated workflows that support capacity planning, routing, scheduling, and resource allocation.

Your work will turn data-driven insights into scalable decision-support tools, dashboards, and well-documented methodologies that enhance field operations.