Medical Graduate jobs in London, ON

ICES Western is seeking a motivated and collaborative Research Data Analyst III to join our team. In this role, you will work closely with researchers and staff to apply rigorous research methodologies using health services administrative data to generate meaningful, policy-relevant insights.

ICES Western is a satellite site of ICES, located within London Health Sciences Centre (LHSC) at Victoria Hospital in London, Ontario. The successful candidate will be employed by LHSC and the London Health Sciences Centre Research Institute, while serving as a legal agent of ICES.

WHY WORK FOR ICES WESTERN?

ICES Western offers a highly collaborative and intellectually stimulating environment where staff and researchers work together to advance ICES' mission: translating data into trusted evidence that informs policy, improves healthcare, and enhances population health. We are highly productive and deeply committed to impactful research. Our work is regularly published in high-impact scientific journals, with authorship opportunities for contributing staff.

Team members engage in diverse research initiatives spanning a wide range of topics. Recent projects have included evaluating dementia care and mortality among individuals experiencing homelessness; assessing surgical outcomes following laparoscopic kidney removal; and examining the association between a commonly prescribed antibiotic and acute respiratory failure in adolescents and young adults.

Rate of Pay: $38.09-$47.60

Hours of Work: 37.5 hours per week

Duration: 1 Year (Possibility for Renewal)

Responsibilities include, but are not limited to:

• Collaborating actively with project teams to provide guidance on research feasibility, study design, methodology, ICES data availability, and interpretation of findings;
• Supporting the development of study designs and detailed analytic plans;
• Developing and maintaining SAS programs to extract, merge, and manipulate data from ICES databases, creating study cohorts in alignment with analytic standards and dataset specifications;
• Conducting exploratory and advanced statistical analyses, and preparing and reviewing outputs for presentation to investigative teams and external partners;
• Maintaining comprehensive and accurate project documentation throughout the research lifecycle;
• Contributing to the preparation of reports, abstracts, peer-reviewed publications, and other knowledge translation products in collaboration with principal investigators;
• Coordinating projects and facilitating effective communication among investigators, trainees, and research staff;
• Applying project management principles to monitor timelines, scope, deliverables, and resource requirements;
• Contributing to the development and maintenance of shared analytic resources, including variable definitions, macros, templates, and documentation of data limitations;
• Identifying, troubleshooting, and resolving data issues as they arise;
• Providing statistical expertise and guidance on study design, analytic plans, and methodological approaches;
• Contributing to project planning and execution, including budget development and management;
• Providing oversight, training, and mentorship to research staff as assigned;
• Maintaining and advancing professional knowledge and technical skills;
• Performing other duties as required to support the effective functioning of the team.

• Master's or Doctoral degree in Biostatistics, Statistics, Epidemiology, Data Science, or a related field, with a strong foundation in biostatistical methods;
• Minimum of five years of experience in statistical programming, SQL and macro development;
• At least two years of experience with health administrative data analysis is an asset;
• Experience applying machine learning methods to population-level or real-world datasets is preferred.
• Strong understanding of health services research concepts, epidemiologic study design, and analysis using administrative health data;
• Advanced quantitative skills using SAS, including proficiency in SQL, macro development, and statistical analysis;
• Demonstrated experience working with large, complex datasets, including merging data from multiple sources;
• Experience applying a range of statistical methods, including logistic (binomial and multinomial), Poisson, negative binomial regression, categorical data analysis, survival analysis, and predictive modelling;
• Ability to learn, adapt, and apply new and existing statistical methodologies as appropriate;
• Familiarity with R and/or Python is considered an asset;
• Strong attention to detail, particularly in following study protocols, developing variables, and resolving data anomalies;
• Ability to clearly communicate complex analytical concepts to non-technical audiences;
• Excellent written and verbal communication skills for reporting and documentation;
• Strong time management and organizational skills, with the ability to prioritize and meet deadlines;
• Demonstrated ability to work independently, exercise sound judgment, and manage competing priorities;
Proven ability to collaborate effectively within a multidisciplinary team environment.