Position Summary
We are looking for a Machine Learning / Data Scientist to lead a healthcare spatial optimization project. You will work with Real-Time Location System (RTLS) data to improve hospital floor space utilization, patient flow, and operational efficiency. This role applies spatial analytics and machine learning to healthcare challenges and contributes to better patient care.
Key Responsibilities
- Analyze RTLS data (patient, staff, equipment movement) to extract patterns and insights.
- Develop and deploy machine learning models for spatial recognition, flow prediction, and anomaly detection.
- Apply clustering algorithms to identify utilization patterns and bottlenecks.
- Build predictive models to forecast demand and optimize resource allocation.
- Perform exploratory data analysis (EDA) on spatial data.
- Design optimization algorithms for hospital layouts and space reallocation.
- Build recommendation engines for dynamic space assignments.
- Develop time-series forecasting models for peak usage prediction.
- Implement reinforcement learning for continuous optimization.
- Build dashboards and geospatial visualizations (heat maps, flow diagrams, reports).
- Use Tableau, Power BI, or web applications to present insights.
- Translate results into actionable recommendations for stakeholders.
- Collaborate with healthcare professionals, architects, and operations teams.
- Support implementation of spatial recommendations and assess ROI.
- Ensure compliance with data privacy regulations (HIPAA, GDPR).
- Apply data anonymization and validation protocols.
- Document methodologies and maintain reproducible workflows.
Requirements
- Master's degree in Data Science, Statistics, Computer Science, Operations Research, or related field.
- 5-7 years of experience in data science or machine learning roles.
- Experience with location-based or IoT sensor data (RTLS preferred).
- Prior exposure to healthcare datasets.
Technical Skills
- Programming: Python or R.
- ML frameworks: scikit-learn, TensorFlow, PyTorch.
- Spatial analytics: GeoPandas, PostGIS, ArcGIS, QGIS.
- Databases: SQL, PostgreSQL/PostGIS, MongoDB with geospatial features.
- Visualization: matplotlib, seaborn, plotly, Tableau, Power BI.
- Strong knowledge of statistics and experimental design.
Domain Knowledge
- Understanding of hospital operations and workflows.
- Familiarity with RTLS technologies (RFID, BLE, WiFi, UWB).
- Knowledge of facility layout and spatial optimization.
- Experience with time-series forecasting.
EA License: R1873481
Company EA License: 11C4879
