Data Analyst (Healthcare)

Requirements

• Educational Background : Bachelor's degree in a quantitative discipline (e.g., Computer Science, Data Science, Statistics); Master's degree preferred.
• Healthcare & Leadership Experience : Minimum 2 years in healthcare analytics or related field; 2-3 years of leadership experience preferred.
• Programming & Analytics Skills : Advanced proficiency in Python, R, SQL; strong experience with statistical techniques, predictive modeling, and data mining methods.
• Visualization & Data Tools : Skilled in data visualization tools like Tableau, Power BI, TIBCO Spotfire, and platforms such as Databricks and AWS.
• AI & LLM Expertise : Experience implementing and fine-tuning AI models, including LLMs, for healthcare applications.
• Software Engineering Skills : Proficient in Docker, Kubernetes, FastAPI, SQLAlchemy, Git, CI/CD, DevSecOps, and handling large datasets.
• Web & App Development : Experience with web frameworks like Streamlit, Next.js, and TypeScript for interactive analytics and application development.
• GMP Recruitment Services (S) Pte Ltd | EA Licence: 09C3051 | VO UYEN AI LINH | Registration No: R22109232
• This is in partnership with the Employment and Employability Institute Pte Ltd ("e2i").
• By applying for this role, you consent to GMP Recruitment Services (S) Pte Ltd's PDPA and e2i's PDPA.

Additional Information

Responsibilitites Lead Data Analytics Strategy : Develop and implement data analytics strategies, including automated data pipelines, ETL processes, and predictive modeling using statistical and machine learning techniques (e.g., LLMs). Data Preparation & Analysis : Clean, validate, and preprocess healthcare data; identify trends and correlations; support clinical research and quality improvement efforts. Dashboard & Tool Development : Build interactive dashboards and intuitive visualizations tailored for non-technical audiences to support data-driven decision-making. Clinical Integration : Collaborate with clinical teams to incorporate analytics into care workflows, including PROMs and care pathway optimization using AI/LLMs. Data Quality & Monitoring : Establish and maintain data validation checks, monitor data integrity, and ensure timely and accurate reporting to stakeholders. Data Governance & Protection : Ensure compliance with data governance policies and regulations (e.g., PDPA, HBRA), enforce security protocols, and oversee responsible AI use. Cross-functional Collaboration : Work closely with internal teams to enhance data visibility, accessibility, and meet evolving data needs across the organization.

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