University of Waterloo

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Data Analyst

Data Analyst

Requisition ID 
2018-2852
Job Category  
Research
Department 
1175 - Propel
Job Status 
Temporary Appointment (Contract)
Hiring Range 
$46,267 - $62,976

More information about this job

Overview

Term: 1 year

 

The Data Analyst works closely with Data Managers, Project Managers, Senior Managers and Investigators to ensure the timely and accurate collection, organization, documentation, analysis and release of data. This position will conduct univariate and multivariate statistical analyses of data using various statistical packages. They will be responsible for the development and maintenance of data sets, and develop and implement quality control processes. They will also participate in paper and report writing for the Centre

 

This role is 28 hours per week (negotiable) and is contingent on funding.

Responsibilities

Career Path Level 9

  • Data Analysis:
    • Analyze data using a range of data analysis techniques including multivariate analyses.
    • Interpret and summarize data for statistical and analytical reports.
    • Work proficiently in at least one statistical package and be familiar with additional packages.
  • Development and Maintenance of Datasets
    • Implement standard operating procedures to create, organize, store, document, extract/export, convert, merge and manipulate complex data files.
    • Develop and implement quality control processes such as validation procedures for monitoring data quality, cleaning and processing data.
  • Teamwork:
    • Take direction well from Investigators, senior Data Analysts, Senior Managers and/or Project Managers.
    • Work independently but have regular interaction with others with regard to specific details of the work.
  • Consultation:
    • Provide consultation for Propel Centre staff regarding data base design and use.
  • Task Organization and Prioritization:
    • Manage the analyses of data from several large and small projects involving various combinations of Investigators and staff.
    • Manage competing priorities and time demands from multiple sources.
  • Communication:
    • Respond to ad hoc and routine data queries.
    • Prepare reports for staff, and Investigators.
    • Contribute to reports for external stakeholders, including funders.

 

Career Path Level 10

 

  • Data Analysis: 
    • Plan and conduct relevant analyses involving sophisticated statistical methods (e.g., multilevel modeling, longitudinal analysis, analysis with multiple measures and clustered data)
    • Use various statistical packages (e.g., SAS, STATA, SPSS) to meet the needs of the analysis and stakeholders.
  • Study Design: 
    • Use statistical methods to contribute to the design of multi-centre studies using complex survey methods and/or longitudinal data across a variety of study types (randomized trials, natural experiments, etc.)
    • Participate with scientists and project managers both at Propel and in other research centres across the country to design relevant research studies
    • Understand new methods for the analysis of natural experiments and randomized studies.
  • Development and Maintenance of Datasets:
    • Develop and implement standard operating procedures to create, organize, store, document, extract/export, convert, merge and manipulate large and small data files.
    • Identify, investigate and resolve data anomalies and discrepancies.
  • Leadership and Teamwork:
    • Supervise and provide direction to Data Managers, Project Managers and students as appropriate.
    • Take direction well from Investigators and more senior Data Analysts.
    • Work independently but in regular communication with other team members including Project Managers, Senior Managers and Investigators.
    • Take responsibility for accuracy of datasets and results.
  • Knowledge Translation: o Contribute to scientific papers.
    • Present findings at scientific meetings.
  • Consultation and Mentorship:
    • Provide consultation for Investigators and staff for study design, data management and analysis.
  • Task Organization and Prioritization:
    • Lead the analyses of data from several large and small projects involving various combinations of Investigators and staff.
    • Demonstrate proficiency in managing competing priorities and time demands from multiple sources.
  • Communication:
    • Respond to ad hoc and routine data inquiries.
    • Prepare reports for Investigators, staff, , data users and internal and stakeholders and funders.
    • Communicate clearly with external stakeholders.

Qualifications

  • Master’s Degree in statistics/biostatistics, epidemiology or equivalent education plus experience
  • This position requires a solid, in-depth knowledge of methods for the design and analysis of data related to different types of population health research and evaluation studies
  • High productivity and proficiency in problem-solving has been demonstrated
  • Experience or familiarity with health behaviour or social science research designs and methods of data analysis preferred
  • Ability to independently plan and implement multivariate statistical analyses (e.g., logistic regression, multiple regression, factor analysis).
  • Knowledge and experience with statistical analyses of cross sectional survey data, is essential
  • Knowledge and experience with longitudinal survey data
  • Knowledge and experience with SAS preferred
  • Knowledge of other statistical packages (e.g., SPSS, S-Plus/R, Stata) is an asset
  • Familiarity with the use of Microsoft Access, Word, and systems-query language (SQL) and data base programming is an asset
  • Strong research skills, including an ability to think critically and analytically, to contribute to scientific papers, proposals for research funding, and to make presentations at scientific meetings
  • Strong writing skills with experience in the preparation of reports, and manuscripts
  • Potential to take an active role in writing scholarly papers for submission to refereed journals
  • Ability to work on multiple projects either independently or under the direction of the PI’s
  • Potential to co-ordinate and supervise data support staff
  • Proven ability to work with data that is confidential in nature