EU remote
Data Analyst
About this role
Location: Hanoi, Vietnam Working Model: Remote/Hybrid Job Description We are looking for a Data Specialist / Health Analytics professional to join a leading healthcare technology and analytics organization. The role focuses on turning complex healthcare data into scalable analytics solutions, reusable data assets and actionable business insights . You will work closely with business, clinical, technology and Data Science teams to solve complex healthcare problems and support data-driven decision making Key Responsibilities Lead analytics initiatives across claims, clinical operations, member analytics, provider performance, population health, care management, medical cost, utilization and outcomes .
Translate complex healthcare and business problems into analytical approaches, metrics and actionable insights. Design and build scalable, big-data analytics systems, data products, dashboards and decision-support solutions . Work with large and complex healthcare datasets, including claims, clinical, member, provider, operational, utilization, cost and outcomes data. Apply analytical and AI-assisted tools to improve productivity and delivery quality.
Collaborate with Data Science/ML teams on feature engineering, model evaluation and interpretation of model outputs . Partner with business, clinical, product, operations, finance and technology stakeholders. Provide guidance and mentorship to junior analysts when required. Requirements Must-have 5+ years of professional experience in health analytics, healthcare data analytics or related analytical roles. Experience in healthcare, insurance, payer, provider, health-tech, life sciences or healthcare consulting environments.
Strong understanding of healthcare data, business processes and analytical use cases. Strong analytical and problem-solving skills with the ability to turn ambiguity into actionable insights. Proven experience building scalable, long-running analytics systems or data products . Strong hands-on experience with large, complex and messy datasets . Advanced proficiency in Python and PySpark . Working knowledge of Machine Learning concepts , including feature engineering, model evaluation and practical application of ML outputs.