Data Analyst (Central Government)

City of London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Position: Data Analyst (Central Government)

Daily Rate: Circa £400-£450 per day, (a status determination assessment has been carried out and the outcome placed the role outside IR35)

Location: Remote/Client Site (as required)

Duration: Initial 16 week contract.

About Triad

Triad is a leading digital and data solutions consultancy, recently awarded Digital Transformation of the Year at the Digital Technology Leaders Awards. We have a proven track record of delivering impactful work that benefits UK citizens.

Role Overview

This project involves reverse engineering complex spreadsheets, documenting their functionality, and translating them into business requirements. The spreadsheets contain numerous formulas and VBA macros, with some VBA code written in German/Austrian.

The successful candidate will work closely with subject matter experts but will be responsible for deciphering the technical details independently.

Key Responsibilities

Reverse Engineering Spreadsheets:

Analyse and document the functionality of existing spreadsheets (ALR, UBA tool, ALAN, ETS analyst tool, registry upload functionality).
Translate VBA macros, including those written in German/Austrian.

Requirement Documentation:

Write detailed business and functional requirements.
Identify and document business rules, calculations, and validations.
Prepare solution-agnostic documentation for the upcoming bespoke development project.

Stakeholder Engagement:

Collaborate with end users and subject matter experts to understand business needs.
Facilitate and manage workshops to gather and refine requirements.
Communicate progress and findings to the delivery manager.

Project Management:

Plan, scope, and manage own workload independently.
Follow an iterative process to progressively refine requirements.
Report progress against the 3-month time frame.

Essential Skills & Experience

Technical Proficiency:

Advanced Excel skills, including extensive experience with formulas and VBA.
Ability to understand and translate VBA code (German/Austrian VBA knowledge is a plus).

Requirement Gathering:

Experience writing detailed business and functional requirements.
Strong documentation skills for business rules, calculations, and validations.

Stakeholder Management:

Experience working with end users to gather requirements and manage expectations.
Strong workshop facilitation skills.

Project Management:

Ability to work independently and manage workload efficiently.
A structured and meticulous approach to documentation.
Iterative process skills, refining requirements over time.

Government Experience:

Proven experience working on central government projects, with an understanding of government operations, regulations, and standards.

Other Information

If this role is of interest to you or you would like more information, please contact Ryan Jordan or submit your application now.

Triad is an equal opportunities employer and welcomes applications from all suitably qualified people regardless of sex, race, disability, age, sexual orientation, gender reassignment, religion, or belief. Triad Group Plc acts as an Employment Business for this contract position

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.