Interim Commissions Analyst

Reading
8 months ago
Applications closed

Related Jobs

View all jobs

Market Research - Data Analyst

Interim Product Performance Data Scientist (FMCG)

Product Performance and Data Scientist

Product Performance and Data Scientist

Product Performance and Data Scientist

Product Performance Data Scientist - FMCG Insights

Interim Commissions Analyst

3-4 months (with potential for permanent opportunities available, subject to sign-off)

£200 - £225pd + holiday pay

2 days working from home, 3 days in the office - Reading outskirts based (free parking, modern offices, near all public transport routes)

We are delighted to be chosen to support one of our key clients, with an urgent interim requirement, initially for 3-4 months. This is a key role that sits in their finance team, for this global organisation, who take immense pride in their products and solutions.

Sitting in the heart of their finance team, you will be ideally available at short notice to start this role, be a UK resident, and be able to offer recent commissions experience. This role will be supporting both the US and UK finance teams.

Key Responsibilities for the successful Commissions Data Analyst:

Own the end-to-end commissions process and commissions forecasting, ensuring accuracy, timeliness, and alignment with their practices
Act as a Business Partner with Commercial Ops, Field Sales, HR, and Finance teams to automate manual processes and streamline data workflows
Develop and maintain dashboards and reports to increase transparency and enable data-driven decision-making
Support EU fleet program by deploying and enforcing policies, managing fleet logistics, data management and generating performance insights
Collaborate cross-functionally to ensure data consistency and system integration between regions
Ensure company compliance with local laws and regulations
Provide backup coverage and support for NA commissions as neededRequired Qualifications:

Bachelor's degree, or higher, in Finance, Business Analytics, Data Science, or a related field
Possibly you will be Certified Compensation Professional (CCP) or similar (but not essential)
3+ years proven experience in finance operations, commissions, or compensation analytics.
Strong analytical and technical skills with demonstrated proficiency in Python, Power BI, SQL, SalesForce or similar CRM, Oracle or similar ERP, commissions applications software, MS Office Suite.
Experience with finance automation tools and process improvement initiatives.Please do get in touch for further information on this superb interim role.

At Gleeson Recruitment Group, we embrace inclusivity and welcome applicants of all backgrounds, experiences, and abilities. We are proud to be a disability confident employer.

By applying you will be registered as a candidate with Gleeson Recruitment Limited. Our Privacy Policy is available on our website and explains how we will use your data

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.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.