Data Scientist

ABOUT HEALTHCARE INC•Saint Paul, MN

25d

About The Position

ABOUT Healthcare is seeking a skilled and innovative Data Scientist to help expand our predictive analytics capabilities and advance our mission to revolutionize hospital operations. This role will work at the intersection of AI/ML, healthcare, and operations to develop and scale machine learning models that deliver actionable insights to hospitals. Any salary range listed for this role represents an estimated base salary only and does not include bonuses, incentives, or other forms of additional compensation.

Requirements

Bachelor’s in data science, Computer Science, Statistics, or related field (or equivalent experience).
3-6+ years of experience developing and deploying machine learning models in production.
Proficiency in Python (or R), SQL, and common ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
Experience working with cloud technologies, particularly AWS (e.g., S3, Glue, Timestream, Bedrock, Nova, sageMaker).
Strong analytical skills and ability to interpret complex datasets.
Knowledge of ETL processes, feature engineering, and real-time forecasting methods.
Excellent communication skills with the ability to present technical concepts to non-technical stakeholders.
Working knowledge of software engineering and data engineering best practices (e.g., version control, testing, modular code, data pipelines), with demonstrated experience collaborating with engineering teams.
Correct business English, including spelling, grammar and punctuation.
Medical Terminology
Health system operating and working models
Business planning and development
Using initiative and independent judgment within established department guidelines.
Contributing effectively to the accomplishment of team or work unit goals, objectives and activities.
Establishing and maintaining effective working relationships with a variety of individuals.

Nice To Haves

Master’s or PhD in Data Science, Computer Science, Statistics, or a related field
Experience in healthcare data analytics or hospital operations.
Familiarity with EHR/EMR data or healthcare interoperability standards.
Knowledge of time-series modeling and ensemble methods.
Exposure to data visualization tools (e.g., Tableau, Power BI).
Understanding of Agile methodologies and collaborative software development.

Responsibilities

Predictive Analytics Development: Build and refine machine learning models for ABOUT products including discharge forecasting, aggregate admission/discharge predictions, patient-level progress tracking, and next level of care predictions.
Data Exploration: Analyze complex healthcare datasets to identify trends, challenges, and actionable opportunities.
Model Deployment: Collaborate with engineers to deploy AI/ML solutions into production, ensuring reliability and scalability.
Collaboration: Partner with product managers, operations teams, and customers to define and implement data-driven features and metrics.
Feature Engineering: Work with AWS infrastructure (S3, Glue, Athena, Timestream, Bedrock, Nova, SageMaker) to contribute to feature pipelines and ensure data used for modeling is reliable, well-structured, and scalable.
LLMs: Demonstrate experience and depth in building products through applying LLMs or other AI domains like NLP, ML or deep learning.
Engineering-Aware Development: Capable of developing, testing, and operationalizing data science and LLM solutions in collaboration with engineering teams, with a strong understanding of production systems and software best practices.
Data Readiness & DevOps Collaboration: Partner with data engineering and platform teams to ensure data availability, quality, and readiness for modeling and analytics. Contribute to data transformations, feature pipelines, and validation logic required to support reliable AI/ML solutions.
Continuous Improvement: Optimize model accuracy and efficiency through testing, monitoring, and iteration.
Documentation and Communication: Present technical findings and recommendations to stakeholders in an easily understandable way.
Perform other duties as assigned.