Senior Data/BI Analyst

Morson Talent
West Horndon
4 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data/BI Analyst

Senior Data Analyst

Senior BI Analyst Developer

Senior BI Analyst

Senior Data Analyst

Senior Data Engineer

Senior Data/BI AnalystLocation: Essex (Hybrid – 3 days onsite)Salary: Up to £70,000A growing company in the manufacturing and engineering sector is transforming how it leverages data. Their Business Relationship Model (BRM) is a powerful relational database connecting all areas of the business, providing real-time insights and historical context on customer and supplier relationships. This system is key to unlocking new revenue opportunities by identifying patterns and connections within their data.They are looking for a highly skilled Data Analyst to help structure and optimize this evolving data framework, uncovering hidden commercial opportunities from complex data interactions. The ideal candidate will have strong technical expertise (Python, SQL, Power BI) and the ability to communicate insights clearly to non-technical stakeholders.What You’ll Be Doing:- Extracting & structuring data: Work with large, complex datasets from multiple sources (including the by-products of ERP systems) to generate actionable commercial insights.- Identifying business opportunities: Analyze interactions between part types, customers, and manufacturing sources to uncover trends that drive revenue.- Creating data-driven strategies: Support procurement, sales, and finance teams by translating insights into clear business recommendations.- Enhancing data frameworks: Help evolve and structure the BRM system to improve real-time decision-making.- Supporting key projects: Work on two major data-driven initiatives, ensuring data integrity and providing analytical support.- Communicating insights: Present findings in layman’s terms to leadership and cross-functional teams, making complex data easy to understand.What We’re Looking For:- Minimum 3 years of experience in data analysis (or exceptional skills if less).- Technical expertise: Strong in Python, SQL, Power BI (experience with relational databases is a plus).- Industry background: Preferred experience in engineering, manufacturing, aerospace, or similar complex industries, but adaptable candidates from pharmaceuticals, nuclear, or other sectors will be considered.- Problem-solving mindset: Ability to connect data points, recognize trends, and provide commercially viable solutions.- Strong communication skills: Comfortable presenting insights to non-technical stakeholders in an actionable way.- Self-motivated & proactive: Can hit the ground running, work independently, and collaborate with multiple teams.Why Join Us?- Drive data transformation in a company evolving its analytical capabilities.- Work cross-functionally with leadership, procurement, sales, finance & project teams.- Impact business strategy by uncovering hidden commercial opportunities.- Hybrid setup – 3 days onsite in Essex, 2 days remote.- Competitive salary up to £70,000.Interview Process:1) 30-minute call with a senior leader.2) Final 1-hour interview with senior leadership.3) Offer & onboarding

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.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.

Machine Learning vs. Deep Learning vs. MLOps Jobs: Which Path Should You Choose?

Machine Learning (ML) continues to transform how businesses operate, from personalised product recommendations to automated fraud detection. As ML adoption accelerates in nearly every industry—finance, healthcare, retail, automotive, and beyond—the demand for professionals with specialised ML skills is surging. Yet as you browse Machine Learning jobs on www.machinelearningjobs.co.uk, you may encounter multiple sub-disciplines, such as Deep Learning and MLOps. Each of these fields offers unique challenges, requires a distinct skill set, and can lead to a rewarding career path. So how do Machine Learning, Deep Learning, and MLOps differ? And which area best aligns with your talents and aspirations? This comprehensive guide will define each field, highlight overlaps and differences, discuss salary ranges and typical responsibilities, and explore real-world examples. By the end, you’ll have a clearer vision of which career track suits you—whether you prefer building foundational ML models, pushing the boundaries of neural network performance, or orchestrating robust ML pipelines at scale.