581 days ago

CHEO (Childrens Hospital of Eastern Ontario)


Ottawa (remote work available)

, Ontario


Job Type:


Degree Level Required:


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CHEO Research Institute  has an immediate requirement for a PhD Data Scientist/ Biostatistician/ Methodologist

As a member of the Clinical Research Unit (CRU), the methodologist/biostatistician will work to ensure rigour and reproducibility in clinical research studies to answer important questions about child health.

The successful candidate will assist and contribute to:

  • Study design
  • Statistical analysis plan design
  • Data analysis in R
  • Overseeing and mentoring other team members
  • Scientific manuscripts
  • Grants
  • Partner with physicians and other child-health clinical researchers to design and implement research studies and analyze research data.
  • Collaborate with CRU team members and researchers on study design, grant writing and data analysis.
  • Write and review code in R to wrangle complex datasets and perform analyses.
  • Mentor colleagues, analysts and interns
  • Prepare and maintain documentation such as analysis plans, project reports and other technical documents.
  • Participate in writing/reviewing manuscripts for publication in partnership with clinician-researchers and with biostatistical-methodological teams.
  • Interact with research coordinators and investigators to understand requirements and to ensure that needs are met.
  • Supervise, support and provide assistance to other statisticians and data analysts to ensure timely delivery of results.
  • Participate in team initiatives to develop and refine standards of practice.
  • PhD in Biostatistics, Epidemiology, or equivalent  (Essential)
  • Research, clinical or operational data science experience (i.e., ≥ 2 year)  (Essential)
  • Knowledge of clinical research designs  (Essential)
  • Strong knowledge of statistical modeling for health research  (Essential)
  • Hands on coding/data analysis experience (in R, SAS, Matlab, Python, Stata etc.)  (Essential)
  • Strong verbal skills to present ideas clearly and concisely to non-technical clients  (Essential)
  • Strong interpersonal skills for research consulting  (Essential)
  • Strong organizational skills: ability to manage competing priorities (Essential)
  • Strong communication skills (both written & spoken  (Essential)
  • Machine learning modeling for health research   (Preferred)
  • Experience with R  (Preferred)


  • Eligible to work in Canada;
  • Compliance with CHEO RI’s Universal COVID-19 Vaccination Policy; and
  • Police Record Check.
Additional Information:

Flexibility to work remotely in a hybrid work model that would include both remote work and on-site work. Candidates living outside of Ottawa are welcome.

Please send a complete CV and cover letter to The Clinical Research Unit, by email to: ClinicalResearchUnit@cheo.on.ca

The CHEO Research Institute values diversity and is an equal opportunity employer. We are committed to providing an inclusive and barrier-free work environment, starting with the hiring process and welcome interest from all qualified applicants. Should an applicant require any accommodations during the application process, as per the Accessibility for Ontarians with Disabilities Act, please notify Human Resources at researchhr@cheo.on.ca.

The CHEO Research Institute seeks to increase equity, diversity and inclusion in all of its activities, including research, education and career development, patient, family and donor partnerships. We value diverse and non-traditional career paths and perspectives, and value skills such as resilience, collaboration, and relationship-building. We welcome applications from members of racialized minorities, Indigenous peoples, persons with disabilities, persons of minority sexual orientations and gender identities, and others with the skills and knowledge to productively engage with diverse communities.

Applications will only be considered from those that are eligible to work in Canada. We thank all applicants for their interest, however, only those invited for an interview will be contacted.




machine learning


clinical research


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