Principal Risk Specialist - Project Controls

Bristol
1 month ago
Applications closed

Related Jobs

View all jobs

Rail Safety Consultant

Graduate Consultant - Specialist Advisory Service

Principal Data Scientist - Generative AI

Registered Manager

Internal Audit Manager - Public & Social Sector

Internal Audit Manager - Public & Social Sector

Principal Risk Specialist - Project Controls
Principal Risk Specialist - Project Controls

The location of the role is Bristol (hybrid working - 2 days per week onsite).
The duration of the contract is 6 months.
The pay rate on offer is £50 - £65 per hour (via Umbrella).

Active SC clearance required - sole British nationals only

Role Summary

The successful applicant will support Major bids and then projects or programmes within our Mission Systems business area.

Principal Risk Specialists are lead-level professional roles in the Risk discipline of the Project Management role family. These roles performs a range of more complex technical or operating activities within this discipline.

The role requires a deeper level of knowledge, skill, and qualifications to perform more specialised work across a broad range of processes, procedures, and systems, working under a moderate degree of supervision from a Line Manager.

Key Responsibilities (day to day duties)

Manage the Risk Management process across the tender(s) and project(s).
Author, implement and maintain the Project Risk Management plan.
Implement Risk Management policies / procedures / process and instructions.
Dependant on lifecycle phase: Establish and implement Risk Management Governance within the project. Maintain Risk Governance arrangements through the project lifecycle.
Plan and conduct risk workshop facilitation.
Management of Risk data, and quality assurance of Risk reporting
Conduct complex quantitative risk analysis and modelling.
Act as the Risk Management Subject Matter Expert on projects
Manage the risk outputs assurance process, including data, analysis and reporting.Additional Responsibilities:

Support the Risk Discipline Lead in generating risk strategies and frameworks.
Develop and implement the project Risk Management Plan
Develop and implement Risk Management policies / procedures / process and instructions.
Develop and assure training material/support to all stakeholders.
Peer review and validate the planning and delivery of highly complex QRA.
Support the Risk Discipline Lead in driving the Risk Community of PracticeExperience/Qualifications/Skills

Essential:

Recent and relevant experience in a similar environment / business sector (complex defence and/or engineering projects/programmes).
Advanced Risk & opportunity management techniques
Experience of implementing Risk Governance, Risk Management methodologies, processes, systems and tools
Full project lifecycle experience
Excellent communication skills to convey complex risk insights to senior stakeholders.
Ability to manage effective relationships with project stakeholders and interfacing functions.
Excellent attention to detail and ability to prioritise and manage tasks effectively.
Practical experience of quantitative risk analysis modelling tools.Desirable:

Experience in conducting integrated RAID management (Risk, Assumptions, Issues and Dependencies)
Knowledge of various contracting methodologies (e.g., FIDIC/NEC/JCT)
Extensive experience of designing and implementing Risk Management methodologies, processes, systems and tools.
The ability to plan, develop and deliver QRA models using appropriate tools to analyse cost and schedule data.
Experience in leading a Risk team.
Experience in improving or implementing risk management approaches.
Familiarity with Risk standards and Risk Governance frameworks
Practical experience using several risk systems and tools.
Batchelors degree level or equivalent qualification
Relevant certifications or qualifications in risk management or related fields

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.