Research Scientist

Fredericton, NB
Hybrid
Posted Oct 1, 2026
1 position

$80,898–$110,256 / year

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Employment type: Full-time
Experience level: Mid-level · 2+ years
Minimum education: Master’s degree
Posting language: English
Working hours: 37 hours per week
Seniority: Mid-Senior level

Job summary

Lead large-scale research and evaluation projects using administrative data, including workforce and occupational health research, and oversee statistical analysis and communication of findings. Supervise and mentor research teams, develop collaborations and funding opportunities, and contribute to DataNB’s strategic planning and sustainability.

Job details

Discover The Opportunity Fredericton, NB Hybrid remote Science and Research Experienced Full-time $80,898 - $110,256 / year Competition Number: 077-26.27 Benefits Health Insurance Dental Insurance Paid Time Off Pension plan Life Insurance Disability Insurance Employee Assistance Program Tuition Aid Closing Date: October 14, 2026 at 4:00 PM DataNB At DataNB we offer a creative, dynamic, and meaningful work environment where all team members are valued. We inform effective practices, programs, and policies in New Brunswick and beyond through collaboration, monitoring, robust evaluations, and knowledge transfer. We are engaged in a wide variety of research/evaluation projects in health, education, and other social sciences sectors. What We Offer Full-time| (1 year) Term | Fredericton | Hybrid UNB is committed to ensuring employees can maintain a healthy work-life balance. As such, we are proud to support a hybrid work approach, which includes flexible hours and work-from-home options. Standard Work Hours: Mon - Fri | 8:15 am - 4:30 pm | 36.25 hours per week Salary Range: $80,898 - $110,256 per annum YOUR FOCUS Reporting to the Director, DataNB, the Research Scientist initiates, designs, leads, and contributes to large-scale mixed methods and quantitative research and/or evaluation projects across a range of areas relevant to the DataNB mandate. The Research Scientist provides senior leadership within the unit and shares in the responsibility of ensuring DataNB's long-term sustainability. This position is also expected to design and lead other activities relevant to DataNB that advance DataNB's mission and objectives. The primary focus of this role will be to support the capacity of the Institute specifically in the areas of workforce and occupational health research, including workers compensation claims data and chronic disease data sets. This role is to facilitate further engagement in research grants and contracts and overall research productivity in the field of occupational medicine and workforce health. Depending on the needs of the Institute, the position may also entail scientific leadership of quantitative administrative data studies. Design and lead large-scale research projects, evaluations, and related initiatives using administrative data sets housed at DataNB. Supervise the work teams of research and/or evaluation staff on specific projects. Conduct statistically analysis and produce tables and figures suitable for publication. Provide leadership and direction to specific research projects and initiatives that are led or supported by DataNB staff. Oversee and lead the creation of research reports and scientific manuscripts for academic publication. Participate and lead in the planning, development, and implementation of new research initiatives. Lead the output, interpretation, and communication of statistical results with internal and external stakeholders. Provide mentorship and supervision to database analysts, research assistants, administrative staff, and junior colleagues, including graduate students and postdoctoral fellows. Contribute substantially to the development and production of the DataNB strategic plan. Develop research and training collaborations with faculty members at UNB and other universities as well as other research partners and organizations. Secure competitive funding to help sustain the ongoing operation of DataNB. Build effective relationships and partnerships within and outside the organization. Manage complex, multi-faceted projects with multiple internal/external stakeholders. What You Bring A PhD in health, epidemiology, biostatistics or a related field. A minimum of 2 years full-time experience in a highly autonomous research role (not including work completed as part of graduate studies). Experience with evaluation projects, systematic reviews and meta-analyses, quantitative research projects, particularly using administrative data, claims data, and data set linkage. Experience or active interest in workplace/ occupational health, claims data, chronic disease, health data, epidemiology. Experience mentoring and/or supervising. Additional Strengths A track record of scholarly achievement such as peer-reviewed publications, conference proceedings and invited presentations of scholarly work is considered a strong asset. Experience working with administrative data/large data sets is considered a strong asset. Experience writing and submitting applications for Tri-Council funding is considered a strong asset. Experience or training with research-based software such as SPSS, Overview, R, SAS, Python, SQL, Stata, NVivo, JMP, REDCap, etc. considered an asset. Experience collaborating across and within various faculties and disciplines is considered an asset. Strong conceptual and analytical skills. Strong knowledge of quantitative methods relevant to public policy and evaluation. Excellent written and verbal interpersonal communication skills. Effective problem-solving and decision-making skills. Ability to work well independently as well as within a team environment. Ability to address and interact with a wide variety of audiences and personalities professionally.

What you’ll do

Requirements

A PhD in health, epidemiology, biostatistics, or a related field and at least two years of full-time experience in an autonomous research role are required. Candidates should have experience with quantitative research, evaluation, administrative or claims data, data linkage, and mentoring or supervision; occupational health experience or interest is relevant.