Data Scientist

Posted 9 Days Ago
Lehi, UT
In-Office
Mid level
Healthtech • Software
The Role
Design, train, and deploy production ML models and scalable data pipelines on healthcare datasets. Build ETL workflows, implement patient-matching algorithms, monitor and tune models in production, and collaborate with engineering, QA, and product teams to ensure data quality, reliability, and stakeholder communication.
Summary Generated by Built In

Data Scientist | AI/Analytics| Lehi, UT| 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.  

 

We’re searching for a Lehi, UT based Data Scientist, to join our AI/Analytics team, so that we can deliver the best tools to satisfy our customer needs around our Patient Experience platform. This is an opportunity to work closely with data scientists, engineers, product leaders, and healthcare experts to design, build, and deploy production machine learning models and scalable data pipelines that power predictive healthcare analytics across a global product suite. 

 

How You’ll Spend Your Time 

  • Own machine learning models end-to-end, from data exploration and experimentation through production deployment, monitoring, and iteration. 

  • Design, train, and evaluate machine learning models using TensorFlow, Keras, and scikit-learn (or equivalent Python ML frameworks) to predict healthcare events and identify patients needing specific treatments, screenings, and interventions across multiple medical specialties. 

  • Work with large-scale healthcare and consumer datasets (millions+ of records) 

  • Build and maintain ETL workflows and data pipelines in BigQuery and Python to ensure data consistency, quality, and usability across complex healthcare datasets including EHR data, medical coding systems, and patient demographics. 

  • Continuously evaluate, tune, and improve models in production through hyperparameter optimization, performance monitoring, and error analysis to maximize accuracy, scalability, and real-world impact. 

  • Implement patient matching algorithms using deterministic and probabilistic techniques to link patient records across disparate healthcare systems. 

  • Partner closely with engineering, QA, and product teams to align models and infrastructure with business goals while maintaining high standards for production code quality and system reliability. 

  • Clearly communicate technical concepts and model results to both technical and non-technical stakeholders to drive data-informed decisions. 

 

What We’re Most Interested in You Having 

  • A bachelor’s or master’s degree in Data Science, Statistics, CS, or a related field. 

  • 3–5+ years of experience in applied data science or machine learning engineering roles, including hands-on experience deploying and maintaining models in production. 

  • Strong proficiency in Python and SQL. 

  • Experience building and training models using frameworks such as TensorFlow, Keras, and scikit-learn, and working with cloud data warehouses such as BigQuery (or equivalent). 

  • Solid understanding of machine learning techniques including neural networks, gradient boosted trees, and ensemble methods. 

  • Strong grounding in statistical analysis, including handling imbalanced datasets, precision/recall tradeoffs, and hypothesis testing. 

  • Experience working with structured and semi-structured healthcare data, including medical coding systems. 

  • Experience designing and deploying data or machine learning systems in a cloud environment (GCP, AWS, or Azure) with an understanding of data security and governance best practices. 

  • Experience with Google Cloud Platform and Vertex AI is a strong plus. 

 

 

By enabling flexibility in how we work and prioritizing employee wellness, we empower our team to do and be their best. Our benefits package includes health, dental, vision, life, disability insurance, 401K, paid time off, and paid holidays. 

 

RLDatix is an equal opportunity employer, and our employment decisions are made without regard to race, color, religion, age, gender, national origin, disability, handicap, marital status or any other status or condition protected by Federal and/or State laws. 

 

As part of RLDatix’s commitment to the inclusion of all qualified individuals, we ensure that persons with disabilities are provided reasonable accommodation in the job application and interview process. If reasonable accommodation is needed to participate in either step, please don’t hesitate to send a note to [email protected].  

 

Salary offers are based on a wide range of factors including location, relevant skills, training, experience, education, and, where applicable, licensure or certifications obtained. Market and organizational factors are also taken into consideration. 

Top Skills

Python,Sql,Tensorflow,Keras,Scikit-Learn,Bigquery,Google Cloud Platform,Vertex Ai,Aws,Azure
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The Company
HQ: Chicago, IL
1,535 Employees
Year Founded: 2018

What We Do

At RLDatix, we believe that what flows through our software is more than bits and bytes — it’s human lives. This is our mantra, our mindset, our passion and our purpose.

We deliver comprehensive healthcare software solutions designed to raise the standard of care for patients, providers and healthcare organizations around the world.

What sets us apart:

🌎 Global reach, local impact — We serve over 10,000 organizations across 30+ countries.

💙 Culture of purpose — Our team is united by the conviction that healthcare work is a privilege.

🤝 Partnership mindset — We see ourselves as more than a vendor; we strive to be a trusted ally in improving patient safety and care.

💡 Innovation-driven — We continuously evolve our platform to help our customers stay ahead in compliance, safety, outcomes and efficiency.

Join us as we continue to empower healthcare systems to do more — for their patients, staff and communities.

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