Role overview
Data Scientist | Product Management | Lehi, Utah | Hybrid
RLDatix (RLD) is on a mission to help raise the standard of care…everywhere. Trusted by over 10,000 healthcare organizations around the world, our solutions help improve health and care. Our applications ensure that patients receive the best and safest care while supporting the providers who deliver it.
Joining TeamRLD means being part of a global effort of over 2,000 team members in making a difference in healthcare…every day.
What you'll work on
- Develop statistical models and machine learning algorithms to support predictive analytics, forecasting, and decision-making in healthcare operations
- Extract, clean, and transform complex datasets using SQL, Python, and modern ETL frameworks in order to deliver reliable, scalable data pipelines
- Design and implement experiments and hypothesis tests to validate product impact and optimize customer outcomes
- Collaborate with engineers, product managers, and clinical experts to translate business questions into data-driven solutions
- Implement monitoring, validation, and alerting tools to ensure data quality, accuracy, and system reliability
What we're looking for
- Mid-level experience in data science, machine learning, or a related role, ideally within SaaS or healthcare
- Proven success in building and deploying end-to-end data solutions (from pipeline to predictive model to production)
- In-depth knowledge of statistical analysis, regression, time-series forecasting, clustering, and experimental design
- Applied experience with SQL, Python (or R), and distributed data technologies (e.g., Spark, Hadoop, Kafka, or cloud platforms such as AWS/GCP/Azure)
- Demonstrated ability to troubleshoot and debug data workflows while maintaining system scalability and availability
- Sincere interest in using data science to improve healthcare outcomes and operational efficiency
- A knack for working collaboratively across technical and non-technical teams in a fast-paced, global environment
Tags & focus areas
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