Data Science Graduate Programme 2022 – applicant brochure
The data science graduate programme is an exciting opportunity for you to work at the heart of public sector data science.
Table of contents
1. What will the Graduate Programme offer you?
The digital revolution is changing everything, transforming how we work and play and how we view societies the world over. Management of data is becoming ever more important in a modern economy. Data Science is driving the development of better public services and improving the lives of citizens in the UK. In order to realise the potential that new data sources hold, we need to be alive
to opportunities as they arise and ensure people have the right skills to unleash innovation through Data Science throughout the public sector.
2. Do you have the passion to work in this Data Science environment?
If so, the graduate programme is a unique opportunity to work at the heart of Data Science in the public sector, to join experienced teams of Data Scientists and contribute towards the real world projects that they are working on. During the two year programme, you will be involved in collaboration and learn from colleagues across the public sector, and practices across government, academia and industry. You will be working on the biggest problems and challenges of our time, using your Data Science skills for the public good.
3. The two-year Graduate Programme
The two-year Graduate Programme includes:
• Training in much valued data science skills and techniques
• Project based learning with high profile public sector organisations including 10 Downing Street and HM Treasury
• Collaboration and networking across the public sector
• Professional development support including mentoring
• Learning from the best in the public sector, industry and academia by attending data science conferences, seminars and events
• A secure foundation to an exciting and rewarding career in public sector data science where you can use your skills for the public good
4. Graduate Programme structure
The first year of the programme consists of 10 training modules, spread over 12 months. Average time commitment in a training month is 3 full working days which may include attending lectures and tutorials, working through independent learning or reading material, and/or assignments. Between these learning sessions you will be working on projects in your home organisation where you will apply your learning within a project context.
The first year of the programme allows you to spend structured time thinking about and practising data science. You will establish a core set of data science skills that complement the specific requirements of your UK government organisation. You will have the opportunity to build collaborative relationships with other graduates and leading UK government Data Scientists.
During the second year of the programme you will work on specific projects that utilise your learning from the first year. You will attend a series of events such as hackathons that encourage your Data Science skill development.
At the end of the programme, you will have acquired new, highly sought-after analytical skills, forming a secure foundation for a future career in public sector data science. You will have demonstrated an aptitude in the effective communication of valuable data insights, having engaged with a wide array of stakeholders. Crucially, the Graduate Programme will have helped you to nurture your passion for cutting edge data science techniques, equipping you for a job with purpose and a stimulating career.
5. Curriculum Overview
The Graduate Programme curriculum provides a robust and exciting framework of learning materials designed to consolidate existing analytical skills. Our experienced lecturers work closely with graduate Data Scientists to continuously review and improve the content of our curriculum, ensuring our training materials are engaging, relevant and effective.
The aim is to provide you with a range of tools and experience in applying them, ensuring that you can make impartial, pragmatic analysis of the most appropriate software or technique in working
towards given success criteria.
Please note: The current sequence of training is under review and is subject to change for 2021 to 2022.
6. Year one
Module one: Data science foundations
A welcome to the curriculum with an introduction to data ethics, data governance and data reproducibility. Introduction to programming is offered and you are expected to complement your programming skills by choosing the framework in which you have least experience at this stage, Python or R. Importing, basic processing and manipulation of data is covered, along with key syntax requirements, conditional flow and framework-specific data structures.
Module two: Designing effective workflows
This module consolidates key programming skills for effective workflow management and improved reproducibility. Command line basics, introduction to Git and GitHub, and writing clean and efficient code introduce key programming skills required for
Module three: Statistics and visualisation
Statistics in both R and Python are offered in this module, both courses providing the opportunity to implement core statistical techniques within a programming framework of their choice. You may choose to sit one or both courses. The data visualisation courses in R and Python prioritise best practice, effective visual communication and visualisation for exploratory data analysis.
Module four: Reproducible code and best practice
Reproducible Open Science assists you in developing robust, well-integrated programs that achieve maximum benefit from programming software. Modular code helps you to consider the utility and structure of your code, ensuring programs are robust and easier to maintain. Unit testing introduces effective, isolated testing practices in the R and Python frameworks.
Module five: Machine learning
Machine learning is introduced with an introductory course, taking a deep-dive into the theory and applications of widely applied machine learning techniques. Programmatic implementation of supervised and unsupervised learning techniques is then taught, using the Python programming framework.
Module six: Natural Language Processing (NLP)
This module aims to build capacity in this much sought after analytical suite of skills. Introduction to NLP will lay the foundation of text analytics within the Python programming framework. Intermediate NLP builds on this learning to develop resilience in basic/probabilistic language models and feature representation.
Module seven: Robust machine learning (ML) models
This module explores evergreen and context-specific quality assurance measures to implement in machine learning models. Quality assurance and principles relating to predictive modelling / machine learning systems are introduced. The material will cover risks across the development cycle of ML models.
Module eight: Data science case studies
Content dedicated to the practical application of data science techniques. Drawing on the expertise in the Data Science Campus projects and research teams, these courses will explore live and ongoing analyses that make use of cutting-edge techniques. You will explore project workflows, helping to embed theory in context and work on the application of skills to case studies.
Module nine: Databases & Big Data
This module’s aim is to equip you with the skills required to apply your prior learning to big data. This includes querying databases to return the required data subsets in Foundations of SQL, ensuring the analysis is efficient and only ingesting the required data.
Module 10: Data Science for Policy
This module takes a boot camp approach to taking a project through from scoping to analysis. This course uses the R framework to help embed prior learning in agile project management, data ethics, data visualisation and effective communication in the form of a written report. The focus is on communication of technical content appropriate to the target audience – policy makers.
7. Year two
Organised events, workshops and seminars stimulate and encourage further learning. You will work on specific projects that utilise your learning from the first year.
We look for candidates who have a passion to work in Data Science, and who have some programming ability in R, Python or another data analysis relevant language.
You must have, or be expected to get at least one of the following:
• a 2.1 degree, or post graduate qualification, in a discipline with numerical or statistical elements.
• equivalent wider experience.
Graduate Data Scientist, Office for National Statistics (ONS) Data Science Campus
‘I was already considering a career change and moving towards data science, and when I found out about this programme, I looked in detail about the modules and it seemed like a great entry point for my new career change.
Before entering the programme, most of my experience was more general data science coding and technical skill was self-taught, I was looking forward to expanding my technical abilities to fill in some gaps in my Python knowledge and some tools for working with big data.
For me I think the fact that the programme is remote has not brought any downsides for me, it is a very positive experience, I haven’t any negatives.
I can say I’ve learnt a lot and I’m generally a better coder and I’m looking forward to the next modules.
And I’ve been very, very impressed by the fact that if you have some coding experience, if you’ve had previous experience, that’s great, that can help you. However, it’s not necessary.’
Data Scientist – HM Treasury
‘So the biggest thing for me was that there was such a big focus on training, often when you were in a role that’s busy, it’s really hard to make time for this.
There are also lots of knowledgeable people to learn from, including those who are delivering the lectures, I really wanted to upskill myself in data science, and it was just a really good opportunity to do that.
I didn’t come from a traditional data science background, but I found that hasn’t been a problem. The course has been here to get you up to speed in the areas that you need to make a career in data science. So that’s been fantastic.
It’s presented a real organisational change for us. We’re hoping that as time goes on, we can be ambassadors for data science within our organisation
The biggest thing I would say is just don’t worry if you don’t have the traditional background for a data scientist, if you haven’t done a degree in computer science or maths. If you’re enthusiastic, I really think that’s the main thing.’
10. Questions from potential applicants
This section includes questions asked by potential applicants who attended a Data Science Graduate Programme webinar in March 2022.
The questions related to work arrangements, the interview and application process and skills.
Will there be specific days I have to attend the lectures because these might clash with my university timetable as a part-time student? What is the minimum number of days you must work?
The taught part of the programme is broken down into modules taught over the first 12 months. Each module is covered over 3 consecutive days, once a month. These days are set at the beginning of the programme and it is an agreement that graduates will be released to undertake learning for these set days and will attend all sessions.
The minimum number of days to work will be discussed at offer stage with the allocated department. These positions can be part-time if required.
Can you expand on the flexible working? Is this more on-site, remote or hybrid type approach?
Flexible working will be in line with the relevant department you are appointed to, this will need to be discussed further with the matched organisation once an offer is made with the individual. But in general terms there are flexible working options of home-working and on-site in line with the business needs of the organisation.
Are we based in teams with other data scientists? What support is there on the placements we are put in?
All the graduate positions are being placed in teams with data scientists and analysts. Graduates will receive the support of their line manager and team to develop and grow into the role of a data scientist. As well as attending the Data Science Graduate curriculum there will be opportunities to undertake projects and training within your allocated department.
Are we going to be given a certificate of completion at the end of the 2 years training?
You will gain a certificate of completion after 2 years. Please note this programme is currently not accredited by an external body.
When will the roles be starting?
For this recruitment round we are aiming for the roles to start in October 2022. This start date is dependent on security clearance and how quickly that goes through. If Security Clearance goes through and you are available to start earlier then some departments might be happy to take you earlier than our planned October date.
Does candidate preference of department (not just location) get taken into account when allocating placements?
We can discuss your preference of department at offer stage and we will definitely try to match you to your preference if that option is available, for example if we have multiple departments offering positions in your chosen location. However this is not guaranteed and will depend on the location that you have stated on your application form.
What opportunities are there after the programme, and can you provide any examples on career advancement?
Data science is a growing profession in the public sector. We are currently working with 29 departments who are building their data science teams, so your skills that you are developing though this programme are going to be in great demand. For the two cohorts that the Data Science Campus recruited, all 12 went on to be promoted either within the Campus or at other government departments. Three from that first cohort have left for opportunities in the private sector. So there is a good retention rate and plenty of opportunity to grow, develop and build your data science career across the public sector.
Interview and application process
How long before the interview do we receive data for the presentation? What programming knowledge are we expected to use?
It is up to you what tools and techniques you utilise to undertake the analysis of the data. You will be asked to describe your approach during the presentation. You are required to have a basic programming experience but there is no requirement to utilise a specific language for the analysis.
Really confused about “name-blind recruitment”. If I remove my name & email plus universities from my CV, how do I write about experiences I gained during study, for example from leading or volunteering?
Remove what you can which is personal to you. We don’t mind company names but please remove University information, ideally be general (University – England, Scotland, Wales ), similarly with Work History (Employment with dates, name, banking company, IT company, marketing, for example). Volunteering organisations can be put like this.
How would recruitment work for Civil Servants. Would it be a secondment or a permanent transfer?
If you are current Civil Servant this will normally be a transfer, but if your current department is willing to release you for a loan, this will need to be determined at offer stage and agreed with both parties. It will depend on the matched offer/department or organisation that are involved. If this is outside of the Civil Service it could be considered as a secondment with agreement of all parties.
Is there any difference in the application process if you are already employed in a government department?
There is no difference in the application process.
What adjustments can be made for applicants with disabilities? What stage should you mention requirements and who can you contact to discuss them?
You have the opportunity to mention details regarding disabilities under the Disability Confidence Scheme, in your application form and we can support you through the process. Please see the advert for information and also the application form for links and guidance, together the relevant fields to complete on how you can be supported.
What might lead a candidate to be considered too experienced to be a good fit for the scheme?
The assessment process is an open and fair competition, so candidates that are interested in this position should apply. The assessment (sift and interview) is scored and offers will be made to successful candidates that have passed at interview. Offers will be made, which may be limited, if there are high volume of passes, in which case, these offers will be made in merit order, until all offers have been accepted. It is the candidate’s decision, to accept if an offer has been made.
What clearance will the positions be? Will there be differing clearance levels for positions or are they all at the same level?
The main level is SC – which is a high level of security clearance. It will depend on the work and projects that each organisation are involved with. There may be some offers where a basic level of security level is needed. Again, this differs per organisation. Please refer to the candidate pack attached to the advert for more information.
Do you offer work visa sponsorship for this data scientist graduate programme?
We can only encourage you to apply. Each case is discussed on a one-to-one basis at offer stage. Sponsorship is ‘limited’ due to the differing security and eligibility requirements for the number of organisations involved.
We encourage all suitable candidates to apply, if they are content they meet the eligibility criteria for living and working in the UK and they have the necessary skills and experience to meet the essential skills of the role. If successful through the process, it will be at offer stage we would discuss personal details and requirements to meet the criteria for a formal offer to proceed.
There are many organisations involved in this campaign each with differing requirements on eligibility, so for candidates that are successful through the process, these details will be discussed further and considered on a case-by-case basis to confirm they meet the criteria to proceed with a formal offer and match to a department. Please note each department has different requirements.
The main factor is candidates will need to be eligible to live and work in the UK. You will need to be based in the UK to take up the post, there are no opportunities to carry out this opportunity whilst living abroad. Be aware as part of the security clearance, this can involve security and police checks for any countries you have lived or worked in over the past five years as a minimum.
How are the core programming skills assessed in the application process?
These will be assessed at sift stage, via your application and the details you present in your application form. It is crucial that you present and evidence your skills in line with the essential skills as in the advert. These will be assessed further at interview stage through the analysis you perform and present.
Is there going to be a preference for the use of either R or Python? What about SAS?
This is dependent on home organisation. During the curriculum you will be able to undertake learning in either R or Python depending on preference.
Do we get to choose to specialise in either natural language processing or general machine learning path?
You will be required to undertake a module in both machine learning and natural language programming.
What level of programming skills and statistics knowledge would be expected in the role?
A basic level of statistics and programming skills are required however both will be covered by the curriculum to an intermediate level.
Is the programme open to recent masters graduates whose undergraduate degree was some years ago?
The programme is open to anyone with a 2:1 or above in a university course at any given time.
I’ve noticed many graduate data scientists in the case studies tend to have a masters. Should I still apply if I only have a BSc or should I get a masters first?
You can apply without a Masters.
Our Graduate Programme vacancies are advertised on Civil Service Jobs.
Social media: Follow @ONSrecruitment on Twitter.