• Excellent opportunity to work with industry experts in the social research space
• Advance your career in survey data processing and social research analytics
• Located next to Flagstaff station

Established in 2000, the Social Research Centre is Australia’s leading provider of social research services and is dedicated to conducting world-class research that informs decision-making and advances our understanding of Australian society. As a wholly owned subsidiary of the Australian National University (ANU), we enjoy unprecedented access to ANU researchers and ANU’s world class research environment.

We are seeking a data scientist to join our Major Projects team. The role works closely with both survey operations and the research teams on all aspects of the survey lifecycle, from sample preparation to the production of complex data outputs. Specifically, the role will be responsible for survey sample preparation, data collection preparation, survey and in-field reminder launches, administration of fieldwork progress, data analysis, tabulation and other reporting.

Our data scientists play a critical role in designing and developing system improvement initiatives that underpin best-practice and flawless execution of complex research projects.

Data scientists may also have supervision responsibilities to more junior members of the team – this will include training, quality assurance and performance management.

Please note that this role is heavily involved in data processing; professional experience in programming in R or Python is essential.

Key responsibilities in this role will include:

• Acquisition and sample management, including working closely with internal and external stakeholders to develop and negotiate specific sample requirements for projects.
• Sample preparation and quality assurance. Tasks include applying tools for automated sample acquisition and real-time validation. This also includes management of mixed-mode multi-dispatch samples such as Dispatch and Collection Control Databases (DACC) and automated status updates across multiple platforms (e.g. Email, SMS, Computer Assisted Telephone Interviewing, online).
• Providing support operations for data collection, including dispatching invitations and reminders to survey respondents, supporting sample adjustments, and responding to issues during field work for surveys.
• Working with research and operations teams to improve process efficiencies.
• Production and quality assurance of outputs, including preparation of electronic files, processing respondent level survey data, self-validation and checking figures and table outputs.
• Design, prepare and construct progress dashboards and reports for clients.
• Support the determination of appropriate sample sizes and survey design. This includes providing descriptions of sampling procedures for reports when required.
• Support survey data coding with advice and issue resolution and assisting with recoding variables and amending datasets as required.
• Technical development tasks (e.g. resolving data queries, evaluating tools and software).
• Assist with the production of training material or survey documentation for clients.

Key Selection Criteria:

• At least two years of professional programming experience (i.e. writing queries) in using R or Python to extract and manipulate large complex data sets. Experience in data manipulation using other programming languages such as SQL, SAS and SPSS would be highly regarded.
• Experience with using MS Office and Windows.
• Experience with validating data from a range of varying sources to ensure adherence to data requirements for reporting.
• Meticulous attention to detail and an ability to identify inaccuracies in data.
• Work in a logical and methodical manner.
• Demonstrated ability to progress multiple unrelated projects/tasks independently.
• Demonstrated ability to handle multiple deadlines without impact quality/timing.
• Ability to think "outside the box" to find creative solutions to problems.
• A team player who is focused on the overall performance of the department/ organisation.
• Well-developed verbal and written communication skills and an ability to communicate complex data concepts to non-technical audience.
• Tertiary qualifications in a relevant discipline, such as Statistics, Computer science, Analytics or Informatics.
• A good understanding of the ethical and legal responsibilities pertaining to data confidentiality and privacy.