Data Analytics

Spearhead the design and execution of end-to-end data analytics strategies.
Develop and manage automated data pipelines and ETL workflows.
Perform data cleaning, preprocessing, and validation to maintain high data accuracy and integrity.
Utilize advanced statistical and data mining techniques to analyze extensive healthcare datasets.
Build and maintain interactive dashboards with user-friendly visualizations tailored for non-technical stakeholders.
Deliver in-depth analytics to support clinical research and quality improvement projects, especially in areas like chronic disease management (e.g., diabetes, kidney disease, asthma).
Create predictive models and deploy machine learning solutions, including large language models (LLMs).
Collaborate with clinical teams to integrate Patient-Reported Outcome Measures (PROMs) into existing care processes.
Work closely with GTO and AIO teams to improve data visibility and accessibility.
Design and apply LLM-based solutions to streamline and optimize patient care pathways.

Data Quality & Monitoring

Conduct regular validation to ensure the integrity and consistency of datasets.
Detect and interpret key trends, patterns, and insights from healthcare data.
Establish and maintain robust data quality assurance and validation protocols.
Generate and present clear, data-driven reports and visualizations to stakeholders.
Ensure all data visualizations are user-centric and accessible to non-technical users.
Liaise with cross-functional teams to gather and address their specific data requirements.

Data Governance & Protection

Implement stringent data security policies and access controls.
Supervise data standardization and quality management initiatives.
Ensure adherence to data privacy laws such as PDPA and HBRA.
Develop secure protocols for safe data exchange and collaborative access.
Promote ethical AI usage and ensure responsible deployment of LLM technologies.

Key Requirements

Bachelor's degree in a quantitative field (e.g., Computer Science, Data Analytics, Statistics)
Minimum of 2 years experience in healthcare analytics or a similar field.
Strong programming skills in Python, R, and SQL.
Hands-on experience with data visualization platforms such as Tableau, Power BI, or TIBCO Spotfire.
Proficiency with cloud analytics environments, especially Databricks.
Solid foundation in statistical methods, including predictive modeling, A/B testing, and time-series analysis.
Skilled in deploying and fine-tuning AI/ML models, including LLMs, within healthcare contexts.
Experience working with cloud providers, particularly AWS.
Familiarity with container technologies like Docker and Kubernetes.
Experience using modern web frameworks such as Streamlit, NextJS, and TypeScript.
Proficient in REST API development using frameworks like FastAPI.
Understanding of database design, with hands-on experience using tools like SQLAlchemy.
Capable of working with large and complex datasets.
Proficient in using Git for version control and collaborative coding.
Strong grasp of CI/CD pipelines and DevSecOps best practices.
Knowledge of medical terminology and healthcare IT systems.
Demonstrated ability to manage stakeholders and drive successful project outcomes.
Excellent analytical thinking and problem-solving capabilities.
Effective communicator with strong presentation, writing, and interpersonal skills.
Highly detail-oriented, with a commitment to accurate data handling and analysis.
Able to convert business challenges into technical data solutions.
Team-oriented, proactive, and capable of thriving under time constraints.
Comfortable working both independently and collaboratively in dynamic environments.

To apply, please visit www.gmprecruit.com

We regret that only shortlisted candidates will be notified.

GMP Technologies (S) Pte Ltd | EA License: 11C3793 | EA Personnel: Bautista Gia Grace De Guzman | Registration No: R23111973

Data Analyst (Healthcare | Contract)