Power & Utilities - Associate Director - Finance - Risk

KPMG International Cooperative; City of Westminster; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading global consulting firm in the City of Westminster is seeking an experienced professional to lead project delivery and provide in-depth quantitative analysis. The ideal candidate will manage client relationships, apply advanced statistical techniques, and spearhead the continuous improvement of analytics processes using R and Python. This role requires strong project management skills, technical expertise in econometric modeling, and a proactive approach to problem-solving, making it essential for the successful navigation of complex financial landscapes related to regulatory frameworks.

Qualifications

• Demonstrated experience in managing projects and trade-offs between time, scope, and quality.
• Proficiency in advanced statistical techniques like regression analysis and stochastic simulation.
• Experience using AI in technical consulting.

Responsibilities

• Lead day-to-day project delivery including quantitative analyses and regulatory submissions.
• Maintain relationships with clients and identify commercial opportunities.
• Implement improvements in quantitative risk modeling platforms.

Skills

Project management

Applied statistics

Econometric modelling

Relationship management

Statistical programming in R and Python

Analytical thinking

Excellent written communication

Education

Undergraduate or postgraduate degree in relevant field

Advanced certifications like CFA, FRM, ACA

Tools

R

Python

Excel

Job description

Responsibilities

• Leading day-to-day project delivery activities, including conducting detailed quantitative analyses, preparing regulatory submissions, drafting well written and clear report and clearly communicating complex analytical results to stakeholders.
• Leading proactively business development, bringing innovative analytical ideas to the team, leading and supporting the drafting of proposals, and participating effectively in client pitches.
• Cultivating and growing client relationships and identifying commercial opportunities to support the client. The ideal candidate will maintain many long-term relationships with clients to understand challenges and shape commercial offerings to support them proactively.
• Deploying a robust understanding of regulatory finance and risk analysis within regulated infrastructure sectors, specifically focusing on the identification and quantification of key risk drivers. These include but are not limited to asset health deterioration, complexity of capital investment programmes, supply chain vulnerabilities, geographical factors, climate‑related impacts, and macroeconomic dynamics such as inflation and interest rate fluctuations.
• Applying advanced statistical and econometric modelling to quantify how each identified risk factor interacts with specific regulatory mechanisms (e.g., cost allowances, incentives, depreciation profiles, and allowed cost of capital). Clearly articulating how these interactions translate into financial exposure and implications for regulated entities across current and future price control periods.
• Leading the implementation and continuous improvement of quantitative risk modelling platforms, including model development, parameter calibration, sensitivity testing, and validation, using programming languages and statistical software such as R (primary) and Python.
• Utilising statistical scenario analysis and stochastic simulation techniques to assess the overall risk profile of regulated entities, explicitly quantifying asymmetries in financial exposure and financeability under varying economic and policy‑driven scenarios.
• Identifying opportunities for and deploying AI into the day to day functioning of the team to continue driving continuous improvements, efficiency and excellence within the team
• Managing simultaneous delivery of multiple projects, ensuring high‑quality analytical outputs that meet both regulatory requirements and client expectations.
• Maintaining an expert‑level understanding of evolving regulatory frameworks, policy developments, and economic trends affecting regulated utilities in the energy and water sectors.
• Staying informed of macro level risks developing and facing the regulated utilities sector more broadly over time is critical to capturing forward looking risk in our analysis. Creative thinking to incorporate forward looking risk utilising third party datasets is particularly critical where risk is changing over time.
• Supporting in managing the team and developing individual members within the team. Specifically managing the long‑term resourcing process for your engagements and the team overall, identifying growth areas for individuals for both the short‑ and long‑term, coaching them to achieve these, providing feedback to all team members routinely during and after each engagement and supporting the recruitment process.

The Person

• Project management skillset and demonstrated experience of running the day to day operation of projects. This includes making trade‑offs between time, scope and quality, managing client and engagement leader expectations, excellent and proactive communication on both progress and outputs, providing guidance to junior team members and reviewing junior team members' work before engagement leader reviews.
• Excellent technical expertise in applied statistics and econometric modelling and data analytics, including proficiency in advanced techniques such as regression analysis, time series modelling, panel data estimation, and stochastic simulation.
• Strong soft skills in relationship management to cultivate and sustain deep client relationships and build the business.
• Strong, demonstrable skills in statistical programming, particularly in R (required) and Python (highly desirable), with practical experience in developing, testing, and validating analytical models for real‑world economic and financial applications. Advanced understanding of Excel formulas and modelling is also required to translate outputs of R based models into client‑ready and user‑friendly interactive dashboards.
• Experience using agentic AI in technical consulting. Ideal candidate would have experience deploying AI in their day‑to‑day work including but not limited to researching technical topics, supporting the development of complex analyses in R or Python based coding and supporting in drafting deliverables. Particular attention to validating AI results is critical.
• High degree of analytical thinking and proven ability to independently tackle complex problems, identify analytical challenges, and develop robust, evidence‑based solutions.
• Strong ability to communicate sophisticated quantitative analysis clearly, persuasively, and succinctly to non‑technical audiences, including regulators, corporate executives, and other key stakeholders.
• Flexible, proactive, and adaptable professional, capable of managing diverse analytical workloads under pressure, responding effectively to client demands, and delivering consistently high‑quality outputs.
• Excellent written communication skills, capable of producing detailed, structured, and compelling technical reports and regulatory submissions.
• Undergraduate or postgraduate degree (minimum 2:1 or equivalent) in Economics, Finance, Mathematics, Statistics, or a related quantitative field. Candidates from other disciplines will be considered if they have sufficient practical experience in advanced quantitative analysis. Advanced certifications like CFA, FRM, ACA are considered highly favourable.