We have big ambitions for the model and want to take its development to the next stage, using it to support the development of a comprehensive anti-poverty strategy. This will involve the creation of impactful analysis to inform the debate around poverty in the UK.

The successful candidate will lead work to develop and cost policy options and present analyses in order to influence senior stakeholders. They will also work with colleagues to develop and enhance the model, with priorities including: greater flexibility in the policy options the model can account for; improved model efficiency; additional functionality to simulate policy impacts over longer timeframes.

RESPONSIBILITIES

Policy simulation and presentation

• Develop and maintain Legatum's knowledge and expertise in microsimulation of poverty impacts.
• Use survey data to create analyses of UK poverty, including the nature and lived experience of poverty in the UK.
• Support the creation of nowcasts: projections of UK poverty, created by using the microsimulation model to update survey data to reflect current macroeconomic conditions.
• Use the microsimulation model to produce a large number of assessments of policy impacts, ensuring these are statistically and economically robust, and appropriately reflect the inherent uncertainties involved.
• Build knowledge and expertise on key aspect of poverty measurement and the drivers of poverty reduction.
• Use results to create impactful written materials that meet the needs of a range of audiences, including summaries for senior management and detailed reports for more technical audiences.

Model development and maintenance

• Working with colleagues, maintain and enhance the existing model by updating the Python codebase to support the requirements of simulating a range of policy scenarios.
• Support colleagues in developing policy options for modelling, including how these can be translated into model-friendly scenarios in the simulator.
• Assist with documentation, creation of user guides and quality assurance processes.

PERSON SPECIFICATION

Experience and knowledge

• Strong data manipulation and analytical skills, ideally rooted in a quantitative degree or field.
• Experience with Python or R. Some experience with the os and subprocess modules (or analogues in R) would be desirable.
• Knowledge of - or interest in - policy issues related to relative poverty and low-income.
• Experience in handling and manipulating large datasets, including UK household surveys (e.g. Family Resources Survey, Understanding Society, Labour Force Survey).
• Some experience with Stata/SPSS/SAS is desirable.
• Experience in producing high quality analysis in written and presentation form.
• Some experience using git for version control would be desirable.
• Excellent general IT skills with experience of MS Office (Excel, Word, PowerPoint) is essential.

Skills

• Strong capabilities in data-driven research, including hypotheses formulation, statistical analysis, and visualisation.
• Ability to ask why of data and consider a variety of outcomes before reaching conclusions.
• Attention to detail, strong awareness of the need for accuracy, quality control and process control.
• Strong written and verbal communications.
• A team player, with strong organisational skills and the ability agree and meet deadlines.

Personal attributes

• Has an optimistic and positive outlook.
• Warm-hearted towards others, willing to help, and generous of time and knowledge.
• Holds oneself and others accountable, committed to doing the right thing.
• Has vision and desire to create value for the long term - willing to be flexible and take risks.
• Self-motivated and able to drive activity forward.
• Eager to learn and easy to coach, seeking-out and considering the opinions of others.
• Good judgement about when to use initiative and when to consult.
• A hard worker who sets ambitious goals and perseveres to achieve them.
• Consistently performs at a high level, pays attention to detail.