Data Analyst

**Requisition #**:25-0028**

**Location**: Cambridge

**Department**: Canadian Institute for Safety, Wellness & Performance

**Payband**: 10

**Payband Range**: $85,529.00 - $106,911.00

**Hours/Week**: 37.5

**Posting Date**: Monday, February 10, 2025

**Closing Date**: Tuesday, March 4, 2025 at 11:59 PM EST

**Vacancy Type**: Administration - Full-time

**Position Summary**:
Reporting to the Director, Research at The Canadian Institute for Safety, Wellness & Performance (CISWP), the Data analyst will analyze complex datasets to support our research initiatives and contribute to the advancement of scientific knowledge in the area of Work and Health.

CISWP's mission is to improve the safety, wellness, and performance of the Canadian labour force by generating knowledge, transferring research to practice, and strengthening workforce development - all in collaboration with stakeholders. CISWP adopts a transdisciplinary and collaborative approach to build capacity for productive and sustainable work. CISWP has state-of-the-art research infrastructure within two major applied research labs and mobile labs equipped with a variety of dedicated field-based and lab-based ergonomic, health and safety, human performance measurement systems, and a full body photogrammetric anthropometry system. The labs are named for their research mandate: START - Skilled Trades Applied Research and Training, and STRIDE - Skilled Trades Research in Inclusivity, Diversity, and Equity.

Learn more about becoming a Data Analyst with CISWP by registering for our upcoming information session and hiring event taking place on Wednesday, February 27, 2025, from noon - 1:00 pm.

**Responsibilities**:
**Data analysis and modeling**
- Analyze primary or secondary data, including biosignals such as EMG (electromyography), ECG (electrocardiography), and motion capture data to assess physical activity, muscle function, and physiological responses
- Perform statistical analysis to identify trends, patterns, and correlations in the data
- Develop predictive models to forecast injury risks and outcomes based on biosignal and injury data
- Combine biosignal data with other data sources (e.g., environmental, ergonomic) to provide comprehensive insights into occupational health risks
- Develop and refine algorithms for processing and analyzing complex datasets, including biosignals and injury statistics

**Data management and quality assurance**
- Gather, organize, and maintain large datasets
- Ensure data quality by cleaning and preprocessing data for analysis
- Develop and maintain databases to ensure data integrity, confidentiality, and security
- Implement and oversee quality assurance processes ensuring data accuracy and reliability
- Integrate data from various sources, including wearable devices, electronic health records, and environmental sensors, to create a comprehensive dataset for analysis

**Reporting and communication**
- Create visual representations of data findings using tools like Tableau, Power BI, or custom scripts in R and Python
- Prepare detailed reports and presentations to communicate findings to partners
- Contribute to academic publications and presentations by providing detailed statistical analysis and interpretations of biosignal and injury data
- Assist in writing grant proposals by providing data-driven insights and justifications for research funding
- Engage with stakeholders, including industry partners, regulatory bodies, and academic institutions, to share findings and collaborate on research initiatives

**Expertise and collaboration**
- Provide guidance on best practices, advanced analytical techniques, and the latest industry trends
- Mentor Junior Analysts and Researchers and contribute to the development of analytical methodologies and protocols
- Work with Researchers and Engineers to understand data needs and provide analytical support
- Assist in designing and conducting research studies, including developing hypotheses and methodologies
- Provide training to team members on data analysis tools, techniques, and best practices
- Ensure all data handling and analysis comply with ethical standards and regulations
- Stay updated with the latest tools, techniques, and trends in data analysis and occupational health research

**Qualifications**:

- Master’s degree in Occupational Epidemiology, Data Science, Biostatistics, Occupational Biomechanics, Public Health or a related field of study is required
- Three years of relevant experience analyzing large data sets as a Data Analyst is required
- Experience with machine learning and predictive modelling is preferred
- Understanding of research design, methods and statistical analysis
- Experience in the use of signal processing software (e.g., MATLAB)
- Understanding of descriptive and inferential statistics
- Comprehensive report writing, presentation and facilitation skills
- Strong analytical and problem-solving skills and ability to communicate and collaborate