About the Role:

We're looking for a Data Scientist to build the analytics and data science foundation for our ordering platform. You'll make the journey of orders from intake to result delivery visible, predictable, and self-correcting. This is a greenfield effort where you will deliver a self-sustaining analytics and data science layer.

What You'll Do:

- Define and build the metrics framework for the digital ordering pipeline.

- Design and deliver dashboards tracking order volume, throughput, turnaround times, error rates, and system stability.

- Build predictive models to forecast order failures, volume trends, and capacity needs.

- Develop automated anomaly detection to surface pipeline issues.

- Apply statistical methods for root cause analysis.

- Partner with engineering teams to instrument data collection.

- Translate complex technical findings into clear narratives for leadership.

- Investigate ad-hoc data questions and document metric definitions and model logic.

Requirements:

- 8+ years of experience in a data scientist, ML engineer, or advanced analytics role.

- Strong foundation in statistics (hypothesis testing, regression, time series, Bayesian methods).

- Advanced SQL skills and proficiency in Python or R.

- Experience with ML libraries (scikit-learn, statsmodels, pandas, NumPy).

- Experience with AWS data/ML services (SageMaker, Redshift, Athena, Glue, QuickSight).

- Hands-on experience with Tableau.

- Demonstrated ability to define metrics frameworks and build dashboards from scratch.

- Experience building anomaly detection or predictive models in production.

- Strong communication skills and experience synthesizing data from disparate sources.

Good to Have:

- Familiarity with healthcare, diagnostics, or lab operations.

- Experience with operational analytics and real-time/streaming analytics (Kinesis, Lambda).