LONDON'S GLOBAL UNIVERSITY Opportunity for data science PhD placements in Department for Education PhD placement opportunities via the Universities Policy Engagement Network (UPEN) are available in the Data Analysis Lab at the Department for Education. The scheme is run by DfE’s Central Analysis Unit, and gives postgraduate students the chance to spend some time working on high-profile analysis and use their skills to guide government policy. Attached please find details of secondment projects available and details of the placement scheme. Funding UCL has potential funding available through the HEIF Knowledge Exchange Fund and UCL Public Policy to support research and students who would be interested in undertaking a placement, subject to eligibility and certain conditions. Eligibility Students who are successfully awarded a placement would generally be expected to interrupt their studentship for the duration of the post and will be funded by the placement award during this time. Candidates must be in a position to return to UCL for a period of six months following the placement to be eligible to apply. To apply please email helen.tsui@ucl.ac.uk with a cover letter explaining your suitability for the placement including the project(s) you are interested in and your availability in 2019 (max 1 page), and a short CV by Monday 6th May 2019. Note: the successful secondees will have to have security clearance, which usually takes at least 8 weeks. If a decision is made in mid-May, the earliest time for the secondment to start might be mid-July, but could well be later.

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Introducing the DfE Data Science Lab The DfE Data Science Lab (DasLab) exists to apply cutting-edge techniques from the fields of machine learning, programming, and data visualisation to tackle the biggest cross-cutting issues problems facing the education system. This secondment is your opportunity to get involved with using data science for public good, directly influencing government policy and gaining invaluable careers experience in the process.

You’ll spend 4 months with us, with half of your time allocated to challenging and advising on our methods and analysis, and the other half on a dedicated data science project of your own. We’ve set out a project shortlist for you to choose from below – choose one that you’re most inspired by and that most fits with your skills, and then get in touch with your university’s UPEN representative for next steps on getting enrolled.

1. Build a tool to predict schools’ KS2 results a year in advance Project description: As a department, we want to get better at proactive (rather than reactive) policymaking. Our Data Science Lab have already developed an experimental tool for forecasting schools’ KS4 results, using XGBoost boosted tree models. In this project, you’ll do the same for KS2 results, and create a model that a host of policy teams across the department can use to inform their work.

Skills involved: R coding; machine learning; data manipulation; exploratory data analysis; basic data visualisation

2. Mining insight from schools’ spending data Project description: The Department for Education holds data on everything that schools spend their money on. This is a hugely rich data source that nobody else has access to. We’re looking for an inquisitive analyst to dive into the data, explore it, develop and test hypotheses, and generate insight we can use to guide our policymaking.

Skills involved: R coding; Data mining; hacking; data exploration; inquisitiveness; ability to generate own research questions from large, complex datasets

3. Which schools have the happiest pupils? Project description: What can schools do to most effectively improve the wellbeing of their pupils? Given the increasing mental health pressures faced by young people today this question is of crucial importance. Tackling this crisis head-on is one of the department’s top priorities, and a key part of

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this is involves building the evidence base around what schools can do to help. This project would involve using survey data on pupils wellbeing along with information about school characteristics and leadership to build a predictive model to help guide policymaking in this area.

Skills involved: R coding; data manipulation; predictive modelling (e.g. regression, machine learning); hypothesis testing

4. Visualise the pathways that disadvantaged groups take through education and into employment

Project desctiption: Disadvantaged groups get worse exam results and are more likely to go on to lower-paid employment than their peers born into more affluent families. Building more research on this key blocker to social mobility is one of the department’s top priorities. To solve this problem, we need to explore innovative ways of describing the current situation to gain a deeper insight of the issue. This project would involve exploring the different pathways taken by different groups through the education system and into employment, uncovering key stories, and creating powerful data visualisations to tell those stories and drive evidence-based policy decision-making.

Skills involved: Advanced data visualisation, built in R (different potential options, e.g. interactive dashboards, animation, infographics, Shiny App development, Sankey diagrams, etc); data manipulation; storytelling & interpretation; presentation skills; behavioural insights (optional)

DfE Central Analysis UnitPhD Placement offer

Make a differenceUse your skills to tackle the issues that really

matter

Social mobility, disadvantage, funding, and much more

Influence policyAccess to senior DfE policymakers

Lead on cutting-edge analysis to drive better policy decision-making

The Central Analysis Unit PhD Placement scheme – what’s in it for you?

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Work on data you can’t get anywhere else

Analyse and explore rich, unpublished government datasets

Answer questions that wouldn’t be possible in any other organisation

Be your own bossFlexible hours

Run your own project

DfE Laptop

Get publishedA final report with your name on it

Opportunities to contribute to high-profile DfE publications

Fire up your careerSenior academic mentoring from DfE’s

scientific Expert advisor

Careers advice, networking and inside intel

Spend 3-4 months on secondment to the Department for Education and kick-start your career

What is the scheme and how do I get on it?

} I haven’t heard of this placement scheme. What’s it all about?} The scheme is run by DfE’s Central Analysis Unit, and gives postgraduate students the chance to spend

some time working on high-profile analysis and use their skills to guide government policy.} Sounds fun. What’s in it for me?} We’ve made a handy graphic to sum this up for you – check out the previous slide.} Sold. How does it work?} You spend 4 months on secondment at the DfE offices in Westminster (flexible & remote working options

available). You’ll spend half your time working on a specific project that you choose in advance, from a list of ideas we’ll put to you. You spend the other half acting as an internal academic consultant – challenging our methods, advising our analysts, and helping to keep us in touch with the cutting edge from academia. You’ll need to secure agreement from your sponsor/department to continue paying your stipend whilst on placement.

} Nice. What skills do I need?} There are two streams: the Research stream, and the Data Science stream.

} For a research placement, you should be studying a social science with a strong quantitative element (e.g. Economics, Psychology, Statistics) – a lot of your work at DfE will be on quant analysis.

} For a Data Science placement, you should be studying either data science specifically or something in a related field – e.g. machine learning, AI, computing, maths, software development, or anything with a strong coding and predictive modelling element

} For either scheme, you’ll need to conduct your analysis in R – so you should either have a solid grounding in it already, or be prepared to learn fast

} Sounds like me. How do I sign up?} Pick a project from the list attached, then get in touch with your university’s UPEN representative to get the

ball rolling!

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