Data Analytics Apprenticeship

Babcock International
Plymouth
1 day ago
Create job alert
About the role

We're on a mission to become a data‑driven organisation, leveraging data to boost productivity, enhance project delivery, and foster a data‑first culture that values data‑led decision‑making.


As a Data Analytics Apprentice, you'll have the opportunity to work on a wide variety of projects, from predictive analysis and mathematical modelling to data visualisation and web development. You’ll partner with teams across the business to develop analytical insights that will inform strategy, improve operational efficiency, and help us deliver on our purpose – to create a safe and secure world, together.


Throughout the programme, you’ll learn to identify and cleanse data from various sources, create performance dashboards, and produce statistical reports. You’ll work closely with stakeholders to ensure data is accurately represented, solving real business challenges with your analysis. By developing strong technical skills and a deep understanding of Babcock’s operations, you’ll play a crucial role in embedding data‑led best practices across the organisation. Use data systems securely to meet requirements and in line with organisational procedures and legislation, including principles of Privacy by Design.


Responsibilities

  • Implement the stages of the data analysis lifecycle
  • Apply principles of data classification within data analysis activity
  • Analyse data sets, taking account of different data structures and database designs
  • Assess the impact on user experience and domain context on data analysis activity
  • Identify and elevate quality risks in data analysis with suggested mitigation or resolutions as appropriate
  • Undertake customer requirements analysis and implement findings in data analytics planning and outputs
  • Identify data sources and the risks and challenges to combination within data analysis activity
  • Apply organisational architecture requirements to data analysis activities
  • Apply statistical methodologies to data analysis tasks
  • Apply predictive analytics in the collation and use of data
  • Collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
  • Use analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
  • Collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
  • Select and apply the most appropriate data tools to achieve the optimum outcome

Qualifications

  • GCSE in any subject, grade C or above
  • English, grade C or above
  • Maths, grade C or above
  • A Level in any subject, grade C or above
  • Share if you have other relevant qualifications and industry experience

Skills & Attributes

  • Communication skills
  • Attention to detail
  • Analytical skills

Security Clearance

Many of our apprenticeship programmes are subject to Security Clearance and Trade Control restrictions, which mean that your place of birth, nationality, citizenship, or residency you hold or have held may impact which programmes you are eligible for. For this programme, you must be able to achieve Baseline Personnel Security Standard (BPSS) and Security Check (SC) clearance. Further details are available at United Kingdom Security Vetting: https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance-levels/national-security-vetting-clearance-levels


About Babcock

Babcock is an international defence company providing support and product solutions to enhance our customers' defence capabilities and critical assets. We provide through‑life technical and engineering support for our customers’ assets, delivering improvements in performance, availability and programme cost. Our ~27,700 employees deliver these critical services to defence and civil customers, including engineering support to naval, land, air and nuclear operations, frontline support, specialist training and asset management. We also design and manufacture a range of defence and civil specialist equipment, from naval ship and weapons handling systems to liquid gas handling systems. We also provide integrated, technology‑enabled solutions to our defence customers in areas such as secure communications, electronic warfare and air defence.


Benefits

Fully funded qualification, personal development training and opportunities; minimum 28 days holiday allowance including bank holidays; competitive pension scheme; employee share scheme; flexible benefits including cycle‑to‑work scheme.


By the end of your apprenticeship, you’ll be ready to take on a variety of roles in Data Analytics at Babcock, where you can expect to earn a competitive salary exceeding £36,000.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Analytics Apprenticeship

Data Analytics Apprenticeship

Data Analytics Apprenticeship

Data Analytics Apprenticeship

Data Analytics Apprenticeship: Kickstart Your Data Career

Data Analytics Apprenticeship: Hands-On Insights & Impact

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.