Project Manager (PM) – TOC Assurance, Heavy Civils - #194010

Job Title: Project Manager (PM) – TOC Assurance, Heavy Civils

Pay: Dependant on Experience

Location: Suffolk/London/Hybrid working

Job ID:2039

Job Purpose / Overview

The Project Manager (PM) – TOC Assurance will support the assurance and validation of Target Outturn Cost (TOC)

submissions across major heavy civils packages at Sizewell C.

This role focuses on detailed commercial and technical review of cost build-ups, procurement strategies, and pre-construction planning to ensure submissions are robust and aligned with programme objectives.

Key Responsibilities

TOC Assurance & Cost Review

– Review detailed TOC submissions including cost build-ups and assumptions

– Analyse contractor pricing, methodologies, and risk allowances

– Identify inconsistencies, risks, and opportunities within submissions

– Support assurance reporting and governance processes

Procurement & Pre-Construction

– Support procurement activities including tender evaluation and clarification

– Review scope, BoQs, and pricing structures

– Ensure alignment between procurement outputs and TOC development

– Assist in contractor engagement and commercial discussions

Commercial & Cost Management

– Contribute to cost benchmarking and validation exercises

– Support development of cost assurance methodologies

– Assist in monitoring cost trends and commercial risks

Stakeholder Engagement

– Interface with commercial, engineering, and delivery teams

– Support workshops, reviews, and assurance panels

– Provide clear and structured analysis to senior stakeholders

Financial (For example: Investments, Funding, Budget or Programme costs)

– General understanding of the Capital Programme budget forecasting along with transition of programme elements back to influence of the costs and budgets

Risk (for example Capital, Project or Performance risks)

General understanding of the capital projects and related risk identification, quantification and analysis

– General understanding of Quantitative Risk Analysis including Monte Carlo simulation for QSRA and QCRA