Data Scientist

In this role, you will play a critical role in building, deploying, and optimizing machine learning models that directly influence business decision‑making. This is a highly visible, hands‑on role with end‑to‑end ownership of model development—from exploratory design through production deployment.

The role is evenly split across:

• Data preparation
• Deployment & performance optimization

(Workload emphasis may shift based on business priorities, but this position maintains consistent involvement across all three areas.)

• Design, build, test, and deploy end‑to‑end predictive and forecasting models
• Develop classification, regression, supervised, and unsupervised ML models
• Perform exploratory data analysis and feature engineering during the first 60 days
• Tune and optimize models for performance, accuracy, and scalability
• Define and track model performance metrics and measurements
• Partner with stakeholders to translate business problems into analytical solutions
• Make data‑driven recommendations and influence final modeling decisions
• Deploy models into production environments and support lifecycle improvements

• Strong data modeling experience with full lifecycle ownership (build → test → deploy → production)
• Hands‑on expertise with Python and/or PySpark (deep, practical usage required)
• Solid background in machine learning, including:
• Classification
• Regression
• Supervised & unsupervised learning
• Cloud experience (Azure preferred)

• Microsoft certifications in AI or Data Science
• Microsoft Fabric experience (preferred);
• Azure Data Factory + Databricks considered acceptable alternatives

• Greenfield AI initiatives with significant investment and executive backing
• High‑impact role with major influence over data and modeling decisions
• Opportunity to take models from concept to production rapidly
• Clear growth trajectory with strong compensation upside