Principal Naval Architect (Weights)

King's Lynn
8 months ago
Applications closed

Related Jobs

View all jobs

Principal Business Intelligence Analyst

Principal Data Consultant - Data Governance

Principal Data Engineer

Principal Data Analyst

Principal Business Intelligence Analyst

Principal Consultant - Data Engineering Lead DBT

Job Title: Principal Naval Architect (Weights)

Location: Barrow-In-Furness, Brough, Filton, Frimley, Manchester, Portsmouth, Weymouth

We offer a range of hybrid and flexible working arrangements – please speak to your recruiter about the options for this particular role.

Salary: Competitive

What you’ll be doing:

Lead the collation strategy for mass properties data to deliver weight and centroid control on multi billion pound submarine programmes

Be responsible for aggregating weight and centroid reports, presenting the status to Chief Naval Architect and generating mitigation plans

Define and manage the mass budgets for submarine programmes and its breakdown to system level

Create and maintain a comprehensive database of parts mass properties

Promote a culture of weight control and work with system engineering to integrate weight as a fundamental design constraint

Conduct Research and Development activities, promoting BAE Systems interests at UK and International Conferences

Perform conceptual parametric estimations for mass distributions and moments of inertia whilst driving the development of methods and tools for mass properties estimation

Provide Subject Matter Expert reviews of weight control methodologies for non-submarine programmes within the BAE Systems group

Your skills and experiences:

Essential

Degree qualified in an Engineering or Mathematics subject or equivalent experience

Ability to work independently and provide technical leadership as part of the team

Experience of weight management

Desirable

Be a chartered Engineer or have the ability to achieve Chartered status within a 12-month time frame

Hold experience of weight control on large programmes

Experience of working with large, complex Electrical or Mechanical systems

Have gained experience using VBA or Python to automate data manipulation tasks

Experience of using CAD packages and programmes

Benefits:

You’ll receive benefits including a competitive pension scheme, enhanced annual leave allowance and a Company contributed Share Incentive Plan. You’ll also have access to additional benefits such as flexible working, an employee assistance programme, Cycle2work and employee discounts – you may also be eligible for an annual incentive.

The Weight Engineering team:

The Weight Engineering Team are a multi-disciplinary Team of Engineers and Data Scientists who estimate, collate and present mass properties data for a number of multi billion pound submarine programmes. The Weight Engineering team are a specialist team who play a critical role in the whole boat design and assuring whole boat safety. We offer relocation support packages across all Submarines roles, subject to meeting eligibility criteria.

Why BAE Systems?

This is a place where you’ll be able to make a real difference. You’ll be part of an inclusive culture that values diversity, rewards integrity, and merit, and where you’ll be empowered to fulfil your potential. We welcome candidates from all backgrounds and particularly from sections of the community who are currently underrepresented within our industry, including women, ethnic minorities, people with disabilities and LGBTQ+ individuals. We also want to make sure that our recruitment processes are as inclusive as possible. If you have a disability or health condition (for example dyslexia, autism, an anxiety disorder etc.) that may affect your performance in certain assessment types, please speak to your recruiter about potential reasonable adjustments.

Please be aware that many roles at BAE Systems are subject to both security and export control restrictions. These restrictions mean that factors such as your nationality, any nationalities you may have previously held, and your place of birth can restrict the roles you are eligible to perform within the organisation. All applicants must as a minimum achieve Baseline Personnel Security Standard. Many roles also require higher levels of National Security Vetting where applicants must typically have 5 to 10 years of continuous residency in the UK depending on the vetting level required for the role, to allow for meaningful security vetting checks.

Closing Date: 4th June 2025

We reserve the right to close this vacancy early if we receive sufficient applications for the role. Therefore, if you are interested, please submit your application as early as possible.

#LI-CB1

#LI-Hybrid

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.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

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.