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Executive (Data Analyst), Clinical & Health Informatics Office - Contract - Job Opportunity at Tan Tock Seng Hospital

Singapore, Singapore
Contract
Senior
Posted: July 12, 2025
On-site
SGD 80,000 - 120,000 per year. This senior-level healthcare data analyst position in Singapore's premium healthcare sector, particularly at a prestigious institution like TTSH, would typically command compensation in the upper range of the local market. The specialized nature of clinical informatics, combined with the requirement for advanced machine learning and NLP expertise, justifies premium compensation levels. Contract positions often include higher base rates to compensate for the lack of permanent benefits.

Key Responsibilities

Drive strategic program evaluation initiatives by conducting comprehensive analysis of rule performance, establishing key performance indicators that directly impact clinical decision-making and patient outcomes
Lead data quality assurance processes by implementing systematic identification and resolution of data quality issues, outliers, and errors, ensuring the integrity of clinical datasets used for critical healthcare decisions
Execute advanced analytics on large-scale healthcare datasets to uncover actionable patterns and trends, delivering executive-level reports and presentations that influence clinical protocols and hospital operations
Collaborate strategically with development teams to optimize Patient Identification Criteria (PIC) algorithms, directly contributing to improved patient care through evidence-based algorithmic enhancements
Oversee the deployment and implementation of PIC algorithms across TTSH infrastructure, ensuring operational efficiency and clinical effectiveness that impacts hospital-wide patient identification processes
Establish continuous monitoring frameworks for algorithm performance, providing strategic recommendations that drive operational improvements and enhance clinical workflows
Architect and maintain executive-level data quality dashboards that provide real-time visibility into performance metrics, enabling data-driven decision making at the organizational level
Conduct sophisticated exploratory data analysis and advanced visualization techniques to extract meaningful insights that inform clinical and operational strategies
Develop and implement cutting-edge machine learning solutions to analyze unstructured clinical data sources, transforming raw clinical notes into actionable intelligence
Deploy Natural Language Processing algorithms on clinical documentation to extract critical insights that support clinical research and quality improvement initiatives
Apply advanced data modeling techniques to create sophisticated decision-making tools that support clinical and administrative leadership in strategic planning
Foster cross-functional collaboration with research teams to identify and communicate data-driven opportunities that advance clinical research and improve patient care
Maintain comprehensive documentation standards for all analytical processes and results, ensuring knowledge transfer and regulatory compliance

Requirements

Education

Bachelor, Master or PhD in Information Technology, Computer Science, or related fields

Experience

Proven working experience as a Data Analyst with a focus on machine learning and artificial intelligence

Required Skills

Information technology training Machine learning and artificial intelligence expertise Experience with machine learning frameworks like TensorFlow, Keras, PyTorch Strong knowledge of statistics Statistical software proficiency in Python, R, or SQL Technical expertise in data models, database design development, text mining and data mining Strong analytical skills with ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy Queries, report writing and presenting findings Ability to set and meet deadlines Ability to work in high-pressure situations Reporting and data visualization skills Excellent attention to detail
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Sauge AI Market Intelligence

Industry Trends

Healthcare informatics is experiencing unprecedented growth as hospitals worldwide accelerate digital transformation initiatives, with clinical data analytics becoming essential for value-based care models and population health management. The integration of AI and machine learning in healthcare settings is driving demand for professionals who can bridge clinical knowledge with advanced analytics capabilities. Natural Language Processing applications in healthcare are expanding rapidly, particularly in clinical documentation analysis and automated coding systems. Healthcare organizations are increasingly investing in NLP solutions to extract meaningful insights from unstructured clinical data, creating significant opportunities for data analysts with specialized healthcare domain knowledge. The shift toward precision medicine and personalized healthcare is creating substantial demand for professionals who can develop and implement patient identification algorithms and clinical decision support systems. Healthcare data analysts with expertise in algorithm development and clinical informatics are becoming critical assets for major healthcare institutions.

Role Significance

Typically leads a team of 3-5 junior analysts and data scientists while collaborating with cross-functional teams including clinical researchers, IT developers, and medical professionals. The role serves as a bridge between technical teams and clinical leadership, requiring strong collaborative skills across diverse stakeholder groups.
This is a senior-level position with significant strategic impact on clinical operations and patient care outcomes. The role combines technical expertise with executive-level responsibility for algorithm development and deployment across hospital systems. The position requires independent decision-making capability and the ability to influence clinical protocols through data-driven insights.

Key Projects

Development and optimization of patient identification and risk stratification algorithms that directly impact clinical decision-making processes Implementation of comprehensive clinical data quality monitoring systems that ensure regulatory compliance and support quality improvement initiatives Creation of advanced analytics platforms that transform unstructured clinical data into actionable insights for clinical research and operational excellence

Success Factors

Ability to translate complex clinical requirements into technical solutions while maintaining deep understanding of healthcare workflows and regulatory requirements Expertise in advanced machine learning techniques combined with practical experience in healthcare data management and clinical informatics applications Strong communication skills to effectively present technical findings to clinical leadership and influence strategic decision-making processes Proven track record in managing high-stakes projects with direct impact on patient care outcomes and operational efficiency Experience in collaborative environments where technical solutions must align with clinical best practices and regulatory compliance requirements

Market Demand

High demand. The convergence of healthcare digitization, AI advancement, and regulatory requirements for data-driven clinical decisions has created exceptional demand for senior healthcare data analysts. Singapore's position as a regional healthcare hub, combined with government initiatives in smart healthcare, further amplifies opportunities in this specialized field.

Important Skills

Critical Skills

Machine learning and artificial intelligence expertise is absolutely essential as healthcare organizations increasingly rely on predictive analytics and automated decision support systems to improve patient outcomes and operational efficiency. The ability to develop, implement, and optimize ML algorithms in clinical settings directly impacts the quality of patient care and hospital performance metrics. Natural Language Processing capabilities are crucial for extracting meaningful insights from clinical documentation and unstructured healthcare data. With the vast majority of clinical information stored in unstructured formats, NLP expertise enables healthcare organizations to unlock valuable insights that drive clinical research and quality improvement initiatives. Statistical analysis and data modeling skills form the foundation for evidence-based clinical decision making and research initiatives. Healthcare organizations require professionals who can apply rigorous statistical methods to clinical data to support regulatory compliance, quality assurance, and clinical research objectives.

Beneficial Skills

Healthcare domain knowledge and clinical informatics experience provide significant advantages in understanding complex healthcare workflows and regulatory requirements, enabling more effective solution design and implementation. Project management and stakeholder communication skills are increasingly valuable as healthcare data analysts must coordinate with diverse teams including clinicians, administrators, and technical staff to ensure successful project outcomes. Knowledge of healthcare regulations and compliance requirements, including data privacy and security standards, becomes increasingly important as healthcare organizations navigate complex regulatory environments while implementing advanced analytics solutions.

Unique Aspects

Integration of clinical expertise with advanced data analytics in a high-stakes healthcare environment where analytical insights directly impact patient care decisions and clinical outcomes
Opportunity to work with comprehensive healthcare datasets spanning multiple clinical domains, providing exposure to diverse medical specialties and complex healthcare workflows
Direct involvement in algorithm development and deployment that influences clinical protocols and patient identification processes across a major healthcare institution
Collaboration with multidisciplinary teams including clinicians, researchers, and IT professionals in advancing healthcare informatics and clinical decision support systems

Career Growth

Progression to director-level positions typically occurs within 3-5 years, with opportunities for rapid advancement given the high demand for experienced healthcare data analytics leaders and the critical nature of clinical informatics in modern healthcare delivery.

Potential Next Roles

Chief Data Officer or Director of Clinical Informatics roles within healthcare organizations, leading enterprise-wide data strategy and analytics initiatives Senior Healthcare Data Science Manager positions overseeing multiple analytics teams and strategic data initiatives across hospital systems Clinical Informatics Consultant roles providing specialized expertise to healthcare organizations undergoing digital transformation initiatives

Company Overview

Tan Tock Seng Hospital

Tan Tock Seng Hospital is one of Singapore's largest and most prestigious public hospitals, serving as a major healthcare institution with over 1,700 beds and comprehensive medical services. As a restructured hospital under the National Healthcare Group, TTSH plays a crucial role in Singapore's healthcare system and serves as a teaching hospital affiliated with medical schools, positioning it at the forefront of healthcare innovation and research.

TTSH maintains a leading position in Singapore's healthcare sector, recognized for clinical excellence and innovation in medical care delivery. The hospital's commitment to advancing healthcare through technology and research initiatives establishes it as an employer of choice for healthcare professionals seeking to work at the intersection of clinical care and technological advancement.
As a cornerstone institution in Singapore's healthcare ecosystem, TTSH serves as a regional reference center and plays a significant role in Southeast Asia's healthcare landscape. The hospital's strategic location and reputation attract top talent and provide opportunities for involvement in region-wide healthcare initiatives and research collaborations.
TTSH fosters a collaborative, mission-driven environment focused on clinical excellence and continuous improvement. The hospital's commitment to innovation and research creates an intellectually stimulating workplace where data professionals can directly contribute to advancing patient care outcomes while working alongside leading medical professionals and researchers.
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