Financial Planning Analyst

Partington
11 months ago
Applications closed

Related Jobs

View all jobs

Assistant Housing Asset Data Analyst

Data Warehouse Developer

Senior Data Strategy Consultant, Marketing Solutions

Data Engineer (Azure)

2x Senior Data Engineer (Financial Services)

Junior Data Engineer

Financial Planning and Analyst

This position is within Sample Management Solutions FP&A team and will be responsible for day-to-day activities including data analysis for financial reporting, forecasting, and planning. Support data-driven decision making by providing management reports & analysis of monthly results and forecasts. Perform work to assist in the analysis of cost structure, profitability, and key performance metrics. Support the development of budgets and forecasts for functional spending areas and perform ad hoc analysis, as needed.

The position is based on site in Irlam, Manchester

What You’ll Do…

Serve as a business partner to the operating team to drive business initiatives, growth, and profitability.

Provide timely, relevant financial information to develop action plans to meet targets.

Financial analysis for Gross Margin, Operating Expenses and Headcount.

Trusted finance operations partner to the business leaders and internal support functions (HR, IT, Facilities, Commercial, Legal, Facilities).

Partner with business unit leaders to drive profitability improvements.

Analyze and interpret data trends and present results.

Improve visibility to costs, lead cost out initiatives.

Prepare margin & variance analysis, understand the impact from cost changes, mix etc.

Develop and report headlight metrics, perform data analysis on key business metrics.

Support development of forecasts, annual operating plan, and multi-year plans.

Monthly / quarterly forecasting and monitoring of risk and opportunities.

High quality Monthly and quarterly management reporting.

Support customer pricing analysis for the division/business units.

Engage with commercial team in deal reviews, provide guidance on pricing, payment terms, highlight and address financial risks proactively.

Develop business cases for growth initiatives in partnership with the business, functional leads, and commercial team.

Drive controllership awareness and compliance with business policies and controls:

Ensure compliance with US GAAP and business accounting policies and procedures.

Develop and maintain processes to support a strong controls environment.

Support internal and external audits.

What You'll Bring

Education: Bachelor’s degree Finance and Accounting, MBA would be a plus.

5+ Years of experience in an FP&A function in a manufacturing environment.

Demonstrated track record of business partnership in a dynamic, high-growth environment.

Excellent interpersonal, verbal/written communication and presentation skills.

Strong process improvement mindset and cross functional engagement. Project management skills. Six Sigma and/or Lean trained would be an added advantage.

Highly proficient in ERP & Financial applications (Oracle, OneStream), Excel skills, PowerPoint, data analytics tools (Tableau, Datawarehouse, Sales Force etc.).

SQL and VBA skills are a plus.

Demonstrate sound work ethic, respect and cultural sensitivity and awareness.

Strong analytical/problem solving skills.

Detail-oriented with the ability to work independently to meet deadlines.

A sense of urgency and self-motivation, with a personal commitment to meeting deadlines.

Occasional travel may be required

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.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.