Sales Data Analyst

Spalding
1 year ago
Applications closed

Related Jobs

View all jobs

Sales Data Analyst – Finance Sector

FMCG Data Analyst & National Accounts (Training Path)

Sales Admin & Data Analyst, UK & Ireland – 10–12 Months

Data Analyst - Fintech SaaS Game Changer. Hybrid

Data Analyst - Fintech SaaS Game Changer.

Data Analyst

Sales Data Analyst
Full Time, Permanent
Spalding
Up to £30,000 P.A Plus Bonus & Excellent Benefits
In a nutshell…
Our client is a leader in manufacturing within the food industry and is looking for a Sales Data Analyst to work alongside the National Account Managers to identify insights and actions to sales activities which will support the promotional process.
The role involves providing product insight to help with business growth and innovation. You will validate data to ensure the alignment with business information whilst maintaining accurate customer sales data. You'll will be at the forefront of dealing with retailers building strong relationships including internal stakeholders.
The ideal candidate will have experience in a sales or data driven role. Backgrounds within a manufacturing environment as a planner / demand / coordinator role will also be considered.
What's involved for the Sales Data Analyst…

  • Monitor orders across production lines
  • Ensure capacity plans are processed accurately
  • Make sure production lines have manufacturing instructions
  • Monitor factory demand and create trend data analysis
  • Schedule works orders and create purchase orders
  • Maintain and monitor inventory levels
  • Communicate any delays with supplier orders
  • Assist line leaders with scheduling orders
  • Suggest improvements to processes
    What you'll need…
  • Experience within a Sales or Data driven role. Backgrounds within manufacturing as a Planner / Coordinator role will also be considered.
  • MS Excel skills
  • Clear communicator
  • Excellent forecasting skills
  • Able to use own initiative and be proactive
    Benefits for the Sales Data Analyst…
  • Competitive salary
  • Pension scheme
  • Bonus scheme
  • Monday - Friday core hours (site based)
  • 25 days + 8 bank holidays
    Should you be interested in this Sales Data Analyst position then please apply within.
    Applications from outside the UK will not be considered.
    3Sixty Resourcing Ltd is an independent recruitment consultancy based in Peterborough supplying permanent and contract personnel across the UK.
    We have a wealth of experience operating in the permanent, temporary and contract industry. We take pride in providing the best customer journey for our clients and candidates covering the following areas: Office, Engineering, Technical, Manufacturing & Construction

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

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.