Data Analyst

BGIS
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Job Title:FM Data Analyst


Purpose of Job
The Data Analyst for the TCE (The Crown Estate) contract at BGIS is responsible for the management and analysis of financial and operational data within the helpdesk function. This role ensures accurate, timely, and compliant financial reporting, data management, and client support across the contract. Working closely with the Contract Performance Manager, Contract Finance Manager, Regional Teams, and sub-contractors, the FM Data Analyst plays a critical role in optimising performance, maintaining data integrity, and driving financial insights across the TCE contract’s three regions.

This role is key to delivering cohesive financial and operational data management while supporting the helpdesk function's day-to-day operations.

Key Responsibilities

Collaboration with Finance and Contract Teams:

Collaborate with the Contract Performance Manager and Contract Finance Manager to provide accurate data analysis and reporting for the TCE contract. Support budgeting and financial planning by ensuring alignment between helpdesk operations and financial strategies. Track Work in Progress (WIP) and share regular updates to ensure accurate financial and operational visibility.

Data and Financial Reporting:

Oversee financial and operational data for helpdesk activities, producing regular reports for both BGIS and the client. Ensure accurate tracking and reconciliation of financial data, supporting compliance with contractual obligations. Prepare weekly and monthly performance reports summarising key contract KPIs, financial performance, and operational trends.

Work Order and Purchase Order Management:

Manage data and financial aspects of work orders, including tracking job progression and processing costs. Oversee purchase order creation and ensure alignment with financial requirements and supplier agreements. Verify compliance of subcontractor invoices and documentation with company policies and contractual standards.

Operational Data Support:

Act as the main point of contact for helpdesk-related data and finance queries from BGIS teams and clients. Maintain and update financial and operational records in the helpdesk system to ensure data accuracy and accessibility. Support the analysis of reactive vs. planned maintenance data to drive efficiency improvements.

Compliance and Documentation:

Ensure all data and financial documentation meet Health & Safety and compliance standards. Archive and maintain site files annually, ensuring accessible and organised records. Oversee the compliance of reactive and planned maintenance records and ensure data accuracy across systems.

Process Improvement and Analysis:

Identify trends and insights from financial and operational data to recommend process improvements. Contribute to the refinement of the AWS process and other data management systems. Support the client’s goals of improving operational efficiency and financial transparency.

Client and Internal Support:

Provide timely support for financial and data queries, both internal and external. Work collaboratively with Regional Teams to ensure contract alignment and operational consistency. Support client and subcontractor relationship management through accurate data and financial insights.

Accountabilities:Reporting directly to the onsitePerformance Manager. Collaborating closely with the Contract Finance Manager to align financial and data reporting with contract goals. Ensuring accurate financial tracking, reporting, and compliance within the TCE contract’s operational framework.Person Specification

Education:

Essential: GCSEs in English and Maths. Desirable: Higher education qualifications (A-levels, HNC/D, or degree level) are advantageous.

Skills / Knowledge:

Essential: Proficiency in Microsoft Excel and other data analysis tools. Strong communication skills, particularly in financial and data-driven contexts. High accuracy in data entry, analysis, and reporting. Ability to work both independently and as part of a team. Desirable: Familiarity with Elogbooks or similar CAFM (Computer-Aided Facilities Management) systems. Knowledge of data and financial processes within the facilities management sector.

Experience:

Essential: Minimum of 3 years’ experience in data and financial analysis for large client contracts. Desirable: Experience in a helpdesk, customer service, or facilities management environment.

Aptitudes:

Detail-oriented and methodical in data analysis and financial reporting. Strong customer focus with a proactive and self-motivated approach. Ability to prioritise tasks, manage time effectively, and meet deadlines under pressure.

Additional Information

This is not an exhaustive list of all responsibilities, duties, skills, efforts, or working conditions associated with the job. The scope of responsibilities may evolve over time to meet the needs of the contract.

At BGIS we believe that diversity and inclusion is a key business driver, such that we never lose sight of its importance as it is woven into the fabric of our organisation. We are committed to maintaining a barrier-free recruitment process by providing equal employment opportunities through recruiting and retention of individuals of all backgrounds. We recognise that promoting diversity is an essential component of our continuing pursuit for organisational success!

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.

Jobs

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.

Education Jobs

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.