We are looking for ambitious Data science professionals to join our Data team, enabling us to have a better understanding of the recruitment challenges within public sectors for specific regions.
The ideal candidates will work with us to develop an insights report around talent landscape in the assigned region. The team will have access to quantitative data such as job advert views, apply clicks etc. and moreover will gather qualitative data through interview. The project will include a desk top review, interviews and insights report that will be presented to our clients operating in the public sector.
If you have experience in mixed-method research while analyzing how trends fit with the national picture and what these trends may tell us about the increasing recruitment challenges that specific regions and sectors are facing, this role is perfect fit for you!
Understand the recruitment trends taking place (primarily over the last year but have access to data from last 3 years)
- Design a data insights report and carry out an initial data collection, to include data from regional public sector organizations; Local Authorities, Health Services, Schools, Fire & Police and use the data to build a picture of the recruitment challenges in specified region and in the public sector
- Explore whether there are different trends/nuances across particular job families/professions (schools education, social care)
- Include any data insights from other data sources such as applicant tracking systems
- Conducting interviews, if appropriate (Contact details will be provided) and carrying out research to gather data to inform the initial insights report. The report will provide an insight into the recruitment challenges facing the public sector across the specified region
- Develop a "Template" approach to enable us to carry out periodic data collection and updated trend report
The expected result of this research project will be to enable public sector organizations to have a better understanding of the challenges faced within the region and use the data insights to work collaboratively to develop solutions.
Most applicable characteristics for this role:
Strong knowledge and understanding of research design principles, including both qualitative and quantitative methods. Understanding the strengths and limitations of each method and how they can complement each other in a mixed-methods approach
Proficiency in both qualitative and quantitative research methods. This includes familiarity with various qualitative data collection techniques such as interviews, focus groups, observations, and content analysis, as well as quantitative methods like surveys, experiments, and statistical analysis
Ability to analyze and interpret both qualitative and quantitative data. This involves using appropriate software and techniques to analyze qualitative data, such as thematic analysis or grounded theory, as well as employing statistical analysis methods for quantitative data
Critical thinking skills to integrate and synthesize findings from different data sources and methods. This includes the ability to identify patterns, connections, and relationships between qualitative and quantitative data, and draw meaningful conclusions from the combined results
Excellent oral and written communication skills to present research findings in a clear and concise manner. This includes the ability to effectively communicate complex concepts and research results to both academic and non-academic audiences
Knowledge of ethical guidelines and standards for conducting research. Ensuring informed consent, protecting participant confidentiality, and addressing ethical issues that may arise during the research process
Strong organizational and project management skills. This involved to plan, execute, and complete research projects within specified timelines
- Ability to work effectively with interdisciplinary teams and stakeholders
Qualifications and Skills:
- Bachelor’s degree or higher in data science, economics, human resources, statistics, or related discipline
- Strong competence with reproducible data analysis using Python or R, Power BI, and Excel.
- Experience in building dashboards using Power BI and Excel
- Strong command over the entire data analysis lifecycle including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation
- Excellent acumen with different types of analysis including descriptive, exploratory, inferential, causal, and predictive analysis