TL;DR

Data Scientist (Medtech): Designing and implementing machine learning models for prediction, classification, and automation in healthcare, with an accent on data-driven impact. Focus on building scalable ML infrastructure and actionable insights from large datasets to support strategic decisions.

Location: Remote across the US, Chile, and Germany.

Company

%hirify_global% is a company focused on placing doctors and patients at the center of care through an intelligent, specialty-specific cloud platform.

What you will do

Design and implement machine learning models and algorithms for prediction, classification, personalization, and automation use cases.
Translate business problems into machine learning solutions, working closely with stakeholders.
Lead cross-functional ML projects, collaborating with product managers, data engineers, analysts, and software engineers.
Analyze large datasets to generate actionable insights, uncover trends, and support strategic decisions.
Develop visualizations, dashboards, and reports to communicate results to technical and non-technical audiences.

Requirements

PhD in Computer Science, Data Science, or a related quantitative field.
Proven track record of research excellence demonstrated by publications in top ML/AI conferences.
Hands-on experience in data science or machine learning in a product or platform-focused environment preferably in healthcare.
Strong proficiency in Python and common ML libraries.
Experience with MLOps tools and cloud-based ML environments such as AWS.

Nice to have

Experience working with healthcare data formats (HL7, FHIR) and privacy standards (HIPAA).
Familiarity with SQL, Spark, and distributed data systems.

Culture & Benefits

Enjoy complimentary office lunches & dinners on select days and healthy snacks delivered to your desk,
Comprehensive health, accidental, and life insurance plans, including coverage for family members, all at no cost to employees,
Annual wellness allowance to support your well-being and productivity,
Earned, casual, and sick leaves to maintain a healthy work-life balance.