台北市信義區1年以上大學
[Purpose of Role]
The Data Processor is a member of our Project Services team, a multi-disciplinary team managing research projects from A to Z, from initial set-up to preparing client-ready deliverables. Within the team, the Data Processor are responsible for analyses and reporting. The position caters for the project deliverables and manages the project from an analytical point-of view. To do this, the Data Processor processes data(bases) in various ways, from manipulating data in analytical tools, to table reporting and charting. Together with the consultant team, the position digs into the project in search of the most important findings. The role supports senior members of the team in analysing and reporting more complex and technical challenging projects.
[Responsibilities and Duties]
Data quality assurance
-Can critically assess the technical side of questionnaires (filters, routings, piping’s, etc.) and can recommend changes to implementation from analyses point-of-view during or after project implementation (e.g., based on database structure, technical check, etc.).
-Guide team members in executing quality checks and act as a knowledgeable sparring partner.
Research Document Development
-Critically revise and finalize the technical side of research doc (filters, routings, pipings, etc.) of surveys with little complexity (e.g., simple quota tree, simple filtering with few conditions, simple routing).
-Recommend changes to implementation from analyses point-of-view during or after project implementation (e.g., based on database structure, technical check, etc.)
Data handling
-Able to independently execute high-level data management (restructuring, merging, complex computations, etc.) to prepare for analyses and charting. For complex datasets, do this with assistance of seniors.
-Able to automate processing of the most common datasets by applying well-known techniques.
-Work efficiently, act as a reference in the domain and is a person to-go-to.
Analysis & Statistics
-Lead for analyzing standard projects and complete the analyses framework where needed and bring in added value independently.
-Able to identify trends and meaningful observations in large sets of data.
-Can apply univariate and bivariate analyses (frequencies, crosstabs, correlations, etc.) on any dataset, varying in complexity.
-Critically look at the dataset and spot new breaks to reveal underlying insights.
-Has a notion of commonly used multivariate analysis techniques.
Reporting & Visualization
-Able to apply commonly used charts and visualizations in the correct way (e.g., stack chart, line chart, etc.). The reporting makes it easy to digest data and attracts the reader to the most important findings.
-Able to set-up, update and maintain common online dashboards. Use different built-in modules to visualize large amounts of data with a complex structure (filtering, time series, etc.)
Account management
-Has a good understanding of the account and what drives client satisfaction.
Method management
-Can critically evaluate standard analysis process and/or steps.
-Can set up technical manuals or a step-by-step guide on how to analyses standard projects.