Research Data Analyst Neurosciences Research Program

Research Data Analyst Neurosciences Research Program (Job ID: 8761)

The primary responsibility of the Data Analyst includes well defined data management tasks such as writing and executing reproducible code for data cleaning, processing, and for conducting descriptive analyses for data science projects. The Data Analyst will use their specialized technical skills to conduct quality checks, format, validate, and standardize data from multiple complex sources, work collaboratively to problem solve, support administrative tasks, and perform descriptive analyses. They may also act as representative of the program to engage with participating sites and other collaborators including researchers to discuss and clarify data requirements.

Don't meet every single requirement? Studies have shown that people in underrepresented communities are less likely to apply to jobs when they don't meet every single qualification. We are dedicated to building an inclusive workplace, so if you're excited about this role but your past experience doesn't align perfectly, we still welcome you to apply.

Duties/Responsibilities

Due to variable nature of position, this list is to be used as a guide only.

Performs Data Management and Data Analysis (80% of work time)

• Lead data processing workflow.
• Identify methodological approaches and the data required to answer specific data science questions.
• Create and develop data management plans for grant submission and project initialization.
• Manages version control of code and documents.
• Update and enhance program's data requirements and all necessary documentation.
• Develop code to conduct analyses to review data quality, generate research output, put final analytic solutions into production.
• Perform quality control checks and data cleaning following standard operating procedures to ensure data is accurate and of high quality.
• Completes cleaning/consistency checks and other quality control measures necessary for the final analysis.
• Analyze the causes of errors and identify and communicate issues with manager and IT to ensure errors/issues get resolved.
• Conduct pre-processing checks against reference standards and models.
• Assist with writing project protocols for data analyses, including protocols for: data extraction, data cleaning, and validation and checks for data quality.
• Conduct descriptive analyses from ad-hoc requests from manager and team.
• Conduct exploratory and descriptive analysis of data to assess feasibility of new data science projects using relevant software/programming language (e.g., R, Python, etc.).
• Create validation files and conduct performance metrics on validation results.
• Develop SOP in consultation with manager, outlining data analysis processes, and resolutions to errors (i.e., a template to be followed to perform standard data analytics, and ways to resolve specific issues).
• Efficiently identify and correct syntax and programming logic errors in code.
• Perform descriptive and inferential statistical analysis in relevant data management, and data analyses software (e.g., R and/or Python). Write HTML/PDF/Microsoft Word reports summarizing the analysis.
• Pre-process raw data to prepare for analysis. This includes cleaning and merging data from multiple sources, as well as understanding overall data quality.
• Pre-process raw data which includes formatting and merging data from multiple sources, as well as understanding overall data quality.
• Respond to ad-hoc requests from team.
• Standardize and harmonize data from data sets to prepare for loading into database (if required).
• Check (validate) any output tables, listings or figures generated to ensure accuracy and reliability of analyses.
• Write HTML/PDF/Microsoft Word reports summarizing the analysis

Data Administration, Documentation, and Communication (20% of work time)

• Provide technical support with any analytics required for interactive dashboards, and reports with interactive visualizations using libraries.
• Attend code review meetings to discuss any problems/solutions to project code bases.
• Collaborate with team and external collaborators to develop new processes and solutions to meet their analytics needs.
• Engage with partners/collaborators to discuss and clarify data requirements.
• Attend meetings with clinicians, researchers, community, and leadership groups to understand project goals and deliverables.
• Meets with research community, and leadership groups, as required, to provide overview on using/interpreting statistical data.
• Explain capabilities and limitations of databases and information to researchers and other stakeholders.
• Maintain and assist with writing/updating standard operating procedures and other documents to support data processing work.
• Identify and notify manager and team of any issues and errors with code/analysis.
• Produce high quality ad hoc and standardized reports customized per project, using relevant software/programming procedures (e.g., in R,Python, etc.), tailored to different end-users (e.g. clinicians, researchers, etc.).
• Support program's data operation needs.
• Write documentation and contribute code to project repositories (e.g., Github/version control) so that all work is reproducible
• Performs Cross Functional and Other Duties as Assigned and/or Requested
• All staff are expected to carry out their assigned duties and responsibilities in a manner which prioritizes patient and employee safety, and confidentiality. Key accountabilities in this regard include:
• Strict compliance with patient/employee confidentiality practices and policies.
• Strict compliance with patient/employee safety practices and standards.
• Appropriate identification, reporting and response to patient/employee confidentiality breaches in accordance with established policies and procedures.
• Appropriate identification, reporting and response to patient/employee safety risks and incidents/events in accordance with established policies and procedures.

Qualifications, Knowledge and Skills

• Bachelor's degree in Computer Science, Statistics/Biostatistics, Engineering, and/or related discipline, required OR demonstrable equivalent combination of specialized education and experience.
• At least 2 years of relevant work experience and computer programming/coding experience in a relevant software/programming/scripting language (R (preferably using tidyverse), Python, or other computer applications. Depending on the unit, the following may be required: experience with ADT and Soarian.
• Experience in healthcare is an asset.
• Fully proficient in the use of relevant programing languages (e.g., R including use of RMarkdown, SAS, LaTeX).
• Data management and/or monitoring experience an asset.
• Demonstrated ability to manage or support statistical programming activities to support research operations (dry, wet, clinical etc.).
• Experience merging and analyzing data coming from multiple sources (e.g., text files, databases, excel etc.).
• Experience using key software and databases such as: Oracle, SQL is an asset.
• Experience working with and manipulating large datasets.
• [Advanced] Must be detail oriented.
• [Advanced] Proficient with MS Office Software (Word, Excel, PowerPoint, Outlook etc.).
• [Intermediate] Strong written and verbal communication.
• [Intermediate] Ability to adapt to changing priorities and workloads.
• [Intermediate] Ability to multi-task and prioritize.
• [Intermediate] Demonstrated ability to work effectively with and communicate with individuals of varying levels of statistical and computer expertise.

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Thank you for applying.