Advisor, Data Science
- Two-year fixed term: 39 hours per week
- Salary range: £30,000 - £45,000 per annum, plus benefits
- Based in Westminster
The Behavioural Insights Team (BIT) is looking for an exceptional candidate to join our new Data Science team in London. The team works to apply data science tools to the development of insights and recommendations that can be turned into practical action by governments in the UK and overseas. This includes machine learning, predictive modelling and data visualisation.
The Behavioural Insights Team
The then Prime Minister created BIT in 2010 to apply behavioural science to public policy in the UK. In February 2014 we became a social purpose company, owned by the Cabinet Office, Nesta (an innovation charity) and our employees.
The Behavioural Insights Team works with governments around the world in almost every area of policy. Whilst the subject and output of our projects varies considerably, there are common threads: we try to understand the contexts in which people make decisions; we notice small details; we find out what has and hasn’t worked before; and we measure everything we do as robustly as we can.
Today the company spans three continents but has the same relaxed and non-hierarchical office culture as it did when it was a team of just eight employees. Though our origins are from within the UK Government, staff at BIT today come from countries across the world. We regularly eat lunch together; play sport; and socialise outside of work time.
As well as displaying professional excellence, BIT selects staff on the basis of our company values: always prioritising social impact; empiricism and humility; fresh thinking, collaboration; and public service.
Roles and Responsibilities
Data Science is a new team at BIT, led by the Head of Data Science and the Chief Scientist. The successful applicant will support the Head of Data Science to help develop BIT’s work with the UK government in this area. The team will work to apply cutting edge techniques from the data sciences to the policy problems. This will include pioneering the use of advanced techniques, such as using machine learning to identify subgroups for which interventions are most effective; identifying trends and patterns in data that suggest where interventions might work; predicting future behaviours by individuals (such as students failing exams, health or social care issues) so that interventions can be targeted most effectively; and designing new interventions that make use of data to personalise messages to help people make better decisions for themselves.
In this role you will conduct research for multiple projects simultaneously, working with other researchers and with policymakers across the team.
This role would suit a candidate with a strong background in econometrics, statistics or computer science and experience working with large datasets.
- A degree (masters or higher) in a relevant subject (such as economics, econometrics, computer science or data science), including significant statistics and econometrics;
- Good working knowledge of R and Stata (this will be tested);
- Experience or substantial training in using and analysing large data sets (such as administrative data) for the purposes of evaluation or predictive modelling;
- Experience with data visualisation tools and packages - visualising data and the results of analysis in a way that makes complex findings accessible and useful to an audience of policymakers and practitioners;
- Ability to interpret complex requirements and work with complex, high-dimensionality data;
- Ability to manage a workload of several projects and to deliver to a high standard on deadline;
- Ability to work collaboratively, with a range of stakeholders in delivery, policy and academic fields;
- An excellent understanding of the behavioural science literature ;
- A good, intuitive understanding of econometrics or statistics;
- The ability to communicate complex topics to a large audience clearly and effectively; and
- Excellent communication skills, including ability to communicate to non-technical and policy audiences.
- A Masters or PhD in a relevant subject area (including, but not limited to, data science, computer science);
- Experience programming (e.g. Python); and
- Experience integrating with APIs.