Strategic Finance Manager

Manchester
4 weeks ago
Create job alert

Strategic Finance Manager

Location: Manchester (Hybrid)

About the Role

Markerstudy Distribution is seeking a Strategic Finance Manager to join our fast-growing and forward-thinking Pricing team. In this key position, you’ll partner closely with senior stakeholders across Finance, Pricing, and the wider business to drive insight, optimise income, and enable robust, data-driven strategic decision-making.

You’ll be instrumental in developing and maintaining our multi-year P&L forecast models and reporting on key financial metrics — ensuring our pricing initiatives translate into tangible commercial success.

About Markerstudy Group

We’re one of the UK’s leading personal lines insurance providers, responsible for:

Insuring 5% of private cars, 20% of commercial vehicles, and 30% of motorcycles in the UK.

Managing a total premium portfolio of ~£1.2 billion.

Powering pricing for household brands including Co-op, Sainsbury’s, Halifax, Saga, Lloyds Bank, O2, and the AA.

We’re investing heavily in cutting-edge technologies, including AI, machine learning, and distributed computing, to build a market-leading pricing capability and Strategic Finance is right at the heart of this transformation.

Key Responsibilities

As Strategic Finance Manager, you will:

Build and manage multi-year P&L forecast models for strategic planning and income optimisation.

Lead financial performance reviews and chair strategic meetings with senior stakeholders.

Support or lead on Financial and Pricing KPI reporting, income optimisation, and product performance analysis.

Collaborate with cross-functional teams to quantify the impact of pricing and commercial initiatives.

Ensure consistency of financial data and forecast assumptions across teams.

Manage and support the development of a Strategic Finance Analyst.

What We’re Looking For

Essential Skills & Experience:

Proven experience in commercial finance or Big 4 transactional services.

Strong financial and data modelling skills (e.g., Excel Power Query, Pivot Tables).

Advanced Excel and PowerPoint skills; comfortable presenting to senior audiences.

Solid understanding of project management and cross-team collaboration.

Highly analytical mindset with attention to detail.

Qualified accountant (ACA / ACCA / CIMA or equivalent).

A strong knowledge of Insurance Broking is highly beneficial

Personal Attributes:

Clear and confident communicator.

Self-motivated with a proactive attitude.

Team player with a passion for innovation and continuous improvement.

Logical thinker who thrives in fast-paced, data-rich environments.

Why Join Us?

Hybrid working from our Manchester office (2 days per week on-site)

Be part of a high-performing team shaping the future of pricing strategy.

Work with household name brands and industry leaders.

Opportunities to grow, innovate, and make a real impact.

A competitive salary and benefits package.

*A full job description is available on application.

Markerstudy Group is proud to be an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees

Related Jobs

View all jobs

Senior Data Scientist - Commercial Analytics London

Senior Data Scientist - Commercial Analytics

Data Analysts

Senior Manager (Data Science)

Financial Data Analyst

Senior Reporting Analyst

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.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.