Data Scientist Degree Apprenticeship (Advisory, Data and Decision Science Team)

Summary

What if you could imagine a better future for us all and a better future for you? With us you can. Our community of over 9,000 employees design and deliver projects such as skyscrapers, train stations, carbon emission reduction and highways that help shape the environment. It inspires us to stay curious, act locally, and think internationally.

Wage: £23,000 a year
Minimum wage rates (opens in new tab)
Training course: Data scientist (integrated degree) (level 6)
Hours: Monday to Friday, 37.5 hours per week. Exact working hours to be agreed.
37 hours 30 minutes a week
Possible start date: Monday 1 September
Duration: 3 years
Positions available: 1

Work

As an apprentice, you’ll work at a company and get hands-on experience. You’ll gain new skills and work alongside experienced staff.

What you’ll do at work

As a Data Scientist Degree Apprentice in our Advisory, Data and Decision Science Team no two days will be the same. During your time as an Apprentice you can expect to develop tools using software such as Python, study applications of statistical techniques and use data and analytical techniques to measure and monitor the impact of projects across the entire asset lifecycle.

Where you’ll work

Wsp House

70 Chancery Lane

London

WC2A 1AF

Training

An apprenticeship includes regular training with a college or other training organisation. At least 20% of your working hours will be spent training or studying.

College or training organisation

NORTHEASTERN UNIVERSITY-LONDON

Your training course

Data scientist (integrated degree) (level 6)

Equal to degree

Course contents

Identify and clarify problems an organisation faces, and reformulate them into Data Science problems. Devise solutions and make decisions in context by seeking feedback from stakeholders. Apply scientific methods through experiment design, measurement, hypothesis testing and delivery of results. Collaborate with colleagues to gather requirements.
Perform data engineering: create and handle datasets for analysis. Use tools and techniques to source, access, explore, profile, pipeline, combine, transform and store data, and apply governance (quality control, security, privacy) to data.
Identify and use an appropriate range of programming languages and tools for data manipulation, analysis, visualisation, and system integration. Select appropriate data structures and algorithms for the problem. Develop reproducible analysis and robust code, working in accordance with software development standards, including security, accessibility, code quality and version control.
Use analysis and models to inform and improve organisational outcomes, building models and validating results with statistical testing: perform statistical analysis, correlation vs causation, feature selection and engineering, machine learning, optimisation, and simulations, using the appropriate techniques for the problem.
Implement data solutions, using relevant software engineering architectures and design patterns. Evaluate Cloud vs. on-premise deployment. Determine the implicit and explicit value of data. Assess value for money and Return on Investment. Scale a system up/out. Evaluate emerging trends and new approaches. Compare the pros and cons of software applications and techniques.
Find, present, communicate and disseminate outputs effectively and with high impact through creative storytelling, tailoring the message for the audience. Use the best medium for each audience, such as technical writing, reporting and dashboards. Visualise data to tell compelling and actionable narratives. Make recommendations to decision makers to contribute towards the achievement of organisation goals.
Develop and maintain collaborative relationships at strategic and operational levels, using methods of organisational empathy (human, organisation and technical) and build relationships through active listening and trust development.
Use project delivery techniques and tools appropriate to their Data Science project and organisation. Plan, organise and manage resources to successfully run a small Data Science project, achieve organisational goals and enable effective change.

Your training plan

You will attend university to study a Data Science degree apprenticeship and gain a bachelors qualification, as well as completing your End Point Assessment with the education provider.
You will be enrolled onto a bespoke internal development programme to help you to attain the knowledge, skills and behaviours to successfully achieve your apprenticeship, and support your career in Data Science.
You will have the support of your team, line manager, mentor and buddy as well as a dedicated early careers team

Requirements

Essential qualifications

GCSE in:

5 GCSEs including English, Maths, Science and IT (grade Level 5 or above)

A Level in:

3 A Levels to include Maths (grade BBB or above)

BTEC in:

Extended BTEC in a relevant subject (grade DDM or above)

Let the company know about other relevant qualifications and industry experience you have. They can adjust the apprenticeship to reflect what you already know.

Skills

Communication skills
IT skills
Attention to detail
Organisation skills
Problem solving skills
Logical
Team working

Other requirements

Candidates must complete the application form in full, answering all specified questions. This is mandatory for all candidates inclusive of their background. Those who pass this initial stage are required to complete an online behavioural assessment. The application form and the behavioural assessment are essential parts of our recruitment process.

About this company

As one of the world’s leading engineering consultancy firms, at WSP we’re passionate about the big questions, and big answers, naturally. For us that’s all about reaching beyond the expected to do work that’ll make a profound impact felt long into the future. We engineer projects that will help societies grow for lifetimes to come. We’ve been involved in many high-profile projects like The Shard, Crossrail, M1 Smart Motorway and the London Olympic & Paralympic Route Network.

http://www.wsp.com/ukapprenticeships (opens in new tab)

Company benefits

Plus 2 paid days a year for volunteering, cheaper gym memberships, discounts with selected high street retailers, 25 days holiday (plus Bank Holidays), WSP's Cycle to Work Scheme, reduced rates on gadget insurance and other benefits.

Disability Confident

A fair proportion of interviews for this apprenticeship will be offered to applicants with a disability or long-term health condition. This includes non-visible disabilities and conditions.

You can choose to be considered for an interview under the Disability Confident scheme. You’ll need to meet the essential requirements to be considered for an interview.

After this apprenticeship

You will gain a Data Scientist degree apprenticeship with a bachelors' qualification. as well as completing your End Point Assessment.
As this is a permanent position, after gaining your degree, WSP will continue to be committed to your learning and development throughout your career with us.
You will have the opportunity to continue professional development and work towards gaining Chartered status or equivalent with your chosen institution, as well as the opportunity to pursue your further study and training goals

Ask a question

The contact for this apprenticeship is:

NORTHEASTERN UNIVERSITY-LONDON

The reference code for this apprenticeship is VAC1000301003.

Apply now

Closes on Monday 31 March 2025

When you apply, you’ll be asked to sign in with a GOV.UK One Login. You can create one at the same time as applying for this apprenticeship.

After signing in, you’ll apply for this apprenticeship on the company's website.

Company’s application instructions

We have a three-stage application process, first you will complete a structured application form that will be reviewed by our talent acquisition team. If you are successful at that stage, you will move on to complete a Behavioural Based Assessment. Finally, if you are successful at this stage, your application will be reviewed by hiring teams and a shortlist of candidates will then move on to an face-to-face interview or interview day with the team you would be working with.

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