We are seeking a dedicated and innovative Scientific Officer to join our team and contribute to the development of the Cancer Data, Impact, and Population Health portfolio at the National University Cancer Institute, Singapore (NCIS). Working closely with the NCIS Associate Director for Data, Digital Health and Informatics, this role involves leveraging data-driven approaches to enhance cancer research, improve patient outcomes, and assess the broader impact on population health. The successful candidate will work closely with multidisciplinary teams to analyze diverse datasets, develop tools for impact assessment, and drive research initiatives that inform public health strategies and policy.
Key responsibilities:
Research Program & Project Management
- Provide strategic input for proposal development and budgeting; lead interdisciplinary research projects on cancer data and population health.
- Plan and coordinate research/project meetings, writing minutes, and follow up on decisions and actions.
- Serve as liaison with NUS/NUHS research offices and external agencies on scientific legal matters (eg. MTA, RCA, service/research agreements, IP etc.)
- Manage collaborations, monitor project timelines and budgets, and ensure effective communication and coordination among all collaborators.
- Contribute to the preparation of research proposals, grant applications, and scientific publications.
Research Grant Management and Coordination
- Assist with grant applications, documentation, and compliance with IRB/DSRB and regulatory requirements.
- Develop and promote external funding strategies for research and academic projects.
- Prepare and submit funding requests, manage budgets, and track grant expenditures.
- Maintain and organize grant documentation, data, and progress reports, ensuring up-to-date compliance policies.
Data Integration, Analysis and Management:
- Oversee the integration and management of diverse cancer-related datasets, including genomic, clinical, epidemiological, and public health data.
- Develop and maintain data repositories, ensuring data quality, integrity, and accessibility.
- Implement data governance frameworks to ensure compliance with regulatory and ethical standards.
- Design and execute data analysis pipelines to extract meaningful insights from large-scale cancer datasets.
- Utilize advanced statistical, machine learning, and epidemiological techniques to assess the impact of cancer interventions on population health, through collaboration with internal and external stakeholders.
Collaboration and Communication:
- Foster strong collaborative relationships with internal and external stakeholders, including researchers, clinicians, and industry partners.
- Communicate complex data science concepts and findings to non-technical audiences effectively.
- Act as a liaison between data science teams and other departments to facilitate knowledge transfer and collaborative initiatives.
- Collaborate with internal and external stakeholders, including oncologists, epidemiologists, public health experts, and data scientists.
Training and Mentorship:
- Provide training and mentorship to junior staff and researchers in data science project management and best practices.
Qualifications:
- A PhD or Master’s degree in Life Sciences, Medicine, Data Science, Bioinformatics or related field
- Strong project management skills, including the ability to manage multiple projects simultaneously using common project management tools.
- Experience with healthcare data, electronic health records (EHR), or cancer research is highly desirable.
- Ability to think critically, solve complex problems, and make data-driven decisions.
- Able to work independently, effectively and a good team player
- Proactive, meticulous, analytical, resourceful and organized
- Demonstrated ability to deliver results to the appropriate quality and timeline metrics.
- Excellent writing and reporting ability
- Excellent communication and presentation skills
- Proficient in Microsoft Suite (including Word, PowerPoint, Excel, Outlook, and Teams), Adobe and Zoom applications
Optional skill: (advantageous but not mandatory)
- Proficiency in programming languages such as Python, R, or SQL.
- Expertise in data visualization tools (e.g., Tableau, Power BI) and statistical software.
