Statistician Social and Socio-economic Sciences

Are you keen to use your quantitative skills in tackling practical problems to improve our environment? BioSS (Biomathematics and Statistics Scotland) is looking for an innovative and motivated early-career statistician or data scientist to join our growing social sciences team. This is an outstanding opportunity to advance your career in a stimulating, supportive environment while tackling engaging and complex societal, environmental, and ecological challenges.

The role offers the chance to develop and apply innovative statistical and data-analytic methods to social science questions relating to the natural environment. Working as part of a collaborative, interdisciplinary team, you will engage with both qualitative and quantitative researchers across BioSS and beyond, and work closely with applied scientists from industry and leading UK research organisations including the James Hutton Institute , Forest Research , and other SEFARI institutes .

We want our staff to have rewarding and engaging careers, and we will support you to develop professionally by building a personal portfolio of research that reflects your interests and ambitions.

BioSS is eligible to apply for UKRI funding,BioSS is eligible to apply for UKRI funding, and we will encourage you to contribute to and develop research proposals with colleagues and collaborators.

This position is a permanent post based at BioSS in Aberdeen
, with flexibility to work from our locations in Dundee or Edinburgh, or remotely from home. At BioSS we value work-life balance and offer a supportive and flexible working environment, with a standard 35-hour working week, self-managed hours and flexible working arrangements that allow staff to structure their working time around organisational needs, to define a healthy work life balance. Staff receive a generous annual leave entitlement of up to 40.5 days per year, together with an employer pension contribution of 15% of salary into a Personal Pension Plan, with flexibility over employee contributions.

We also provide access to a confidential Employee Assistance Programme offering support to employees and their families with work-related or personal issues.

• Deliver collaborative research and statistical consultancy in the application areas of social science and socio-economics.
• Deliver innovative research, developing social science statistics/data analytic methods with potential relevance to the RESAS-funded Strategic Research Programme.
• Support more senior staff in seeking and winning external funding for research and consultancy projects.
• Contribute to the development of a distinct group of quantitative scientists within BioSS focused on quantitative social science.
• Represent BioSS at meetings with stakeholders from scientific and non-scientific backgrounds, expanding our collaborative network.
• Engage with government agencies, NGOs, universities, research institutes and commercial organizations.
• Contribute to the development and delivery of BioSS training courses for scientists.

What We’re Looking For:

Essential

Qualifications & Skills:

• A PhD in statistics or another closely related quantitative discipline, or an MSc with commensurate post-qualification development and work experience.
• Experience with developing, and applying, modern statistical methods to real-world problems in the social sciences.
• Evidence of ability to initiate, manage and maintain scientific collaborations, and an ability to work independently.
• Broad familiarity with the current statistical methods used in social and socio-economic research.
• Enthusiasm for promoting the use of statistical methods to aid research in the social and socio-economic sciences, and for interacting with applied scientists.
• Strong general statistical skills, and an understanding of relevant statistical methods, including survey design, mixed models, generalised linear models, longitudinal modelling, and multivariate analysis.
• Proficiency in statistical programming (for example, in R).
• Evidence of good written communication.
• Ability to give effective spoken presentations, to both quantitative and wider scientific audiences.

Desirable skills and experience:

• A broad range of areas of statistical experience and expertise would fit the remit of the post well, including:
  • statistical design of social-science studies, including survey design
  • ordinal regression
  • latent variable models
  • statistical graphical modelling
  • causal inference
  • model-based integration of data…