Data Scientist at Helium Health

Role Overview:

• As a Data Scientist at Helium Health, you will play a pivotal role in harnessing the vast amount of healthcare data we collect to develop predictive models, optimize clinical workflows, and support critical decision-making. You will work closely with data engineers, clinicians, and product teams to build data-driven solutions that directly impact the healthcare industry. This is an exciting opportunity to apply advanced machine learning, statistical analysis, and AI techniques to improve patient care and operational efficiency.

Responsibilities:

Data Science

• Create data science strategies that align with the company's goals and objectives. 
• Analyze large, structured, and unstructured healthcare datasets (e.g., clinical, administrative, and claims data) to discover insights, trends, and opportunities.
• Develop predictive models, such as patient risk stratification, readmission prediction, and disease progression modeling, using machine learning and statistical techniques.
• Build and deploy algorithms that improve clinical decision-making, including natural language processing (NLP) for extracting insights from clinical notes and other text-based data.
• Collaborate with healthcare professionals to understand clinical workflows and design solutions that enhance patient outcomes.
• Design and implement A/B testing frameworks to evaluate the effectiveness of new interventions or system features.
• Create data visualizations and reports to communicate key findings to stakeholders, including clinicians, healthcare administrators, and product teams.
• Ensure the quality, integrity, and compliance of all data processes, aligning with regulations such as HIPAA and HITECH.
• Work closely with data engineers to optimize data pipelines and develop scalable solutions for real-time analytics.
• Stay current with the latest developments in data science, AI, and healthcare technology to apply cutting-edge methods to healthcare problems.

Business Intelligence

• Partner with business to provide insightful analytics to improve processes; explore opportunities for analytics.
• Assist in translating complex datasets into strategic insights for the business; communicate to non-technical audiences, visualize results, and create understandings and solution buy-in.

People Management

• Lead the team of data scientists and analysts in the development and implementation of data science projects.
• Participate in peer review of requirements and code review with the larger team.

Requirements

• Master’s or BSc. in Data Science, Statistics, Computer Science, Biomedical Informatics, or a related field.
• 3+ years of experience in data science or machine learning, preferably in healthcare or EHR environments.
• Proficiency in programming languages such as Python or R, along with SQL for data manipulation.
• Proficiency in the development, validation, implementation, and production launch of machine-learning algorithms and models.
• Strong expertise in machine learning algorithms (e.g., regression, decision trees, clustering, neural networks) and experience with libraries such as TensorFlow, Scikit-learn, or PyTorch.
• Experience working with healthcare data standards and formats (e.g., HL7, FHIR, ICD codes, claims data).
• Knowledge of statistical analysis and experimental design, including A/B testing, hypothesis testing, and survival analysis.
• Familiarity with data visualization tools (e.g., Tableau, Power BI, or Matplotlib) to present insights clearly to non-technical audiences.
• Experience with natural language processing (NLP) for extracting insights from clinical notes and medical documents is a plus.
• Strong problem-solving and communication skills, with the ability to work effectively in cross-functional teams.
• Knowledge of healthcare regulations and standards (e.g., HIPAA, HITECH) and the importance of data security and privacy.
• Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation
• Deep appreciation for diversity of thought and a proponent for collaborative solutions.
• Ability to communicate technical concepts and solutions at a level appropriate for technical and non-technical audiences.

Preferred Qualifications

• Experience working with EHR systems and clinical data workflows
• Familiarity with cloud platforms (AWS, Azure, GCP) for deploying machine learning models and scalable data solutions
• Prior experience with time-series analysis, predictive modeling or deep learning techniques in healthcare
• Strong understanding of healthcare operations, including clinical decision-making, patient management and population health.