Data Analytics & Data Science Lead

Birmingham
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Analytics & Data Science Leader — UK (Hybrid)

Data Science Lead 1

Data Science Lead 1

Game Analytics Data Scientist – Insights & ML

Managing Consultant, Customer Data Analytics / Data Science

Chief Commercial Data Science & Analytics Leader

Michael Page have exclusively partnered with The Government Property Agency (GPA) to support on their continued Data Transformation programmes. The newly created role of Data Analytics & Data Science Lead is pivotal in this strategy

Client Details

Government Property Agency

Description

Introduction:

Michael Page have exclusively partnered with The Government Property Agency (GPA) to support on their continued Data Transformation programmes. The newly created role of Data Analytics & Data Science Lead is pivotal in this strategy. The GPA is the largest property holder in government, with more than £2.1 billion in property assets and over 55% of the government's office estate.

The GPA are transforming the way the Civil Service works by creating great places to work, leading the largest commercial office programme in the UK, working towards halving carbon emissions from government offices, and achieving greater value for taxpayers. The team are seeking innovative, solutions-focused people to work on leading transformational programmes such as the Government Hubs Programme, Whitehall Campus Programme and Net Zero Programme, as well as delivering modern, cost-effective real estate service solutions.

Innovation and progress are at the heart of GPA behaviours, fostering a culture of lifelong learning, where curiosity and self-improvement are encouraged. The organisation is dedicated to becoming a leading, inclusive employer both in the external market and throughout the Civil Service. A strong emphasis on Equity, Diversity, and Inclusion (EDI) is not just about driving inclusion across our organisation, it is also about ensuring the services meet the needs of government departments and the civil servants work environments.

Job Overview:

Data analytics combined with Data Science can provide a transformational and powerful combination to support GPA's current and forward planning in key areas such as across Operations, Portfolio Performance, H&S, Risk Management and Sustainability. It provides essential actionable insights to support planning, decision making, scenario planning and predictive analytics.
Data analytics across the GPA is already providing a transparent, interactive interface to the large amount of data collected and processed in GPA. Because of the demand and high importance of data analytics & reporting, a lead role is needed to manage the portfolio of work and the velocity and variety of the data within GPA.
A number of exemplar PowerBI dashboards are already supporting business plan objectives and crucial reporting in areas such as Occupancy, Property Portfolio, Customer Satisfaction, Client Satisfaction, CRM Reporting, Sustainability etc.
Additionally, the GPA would benefit from developing capability in data science. This is closely related to data analytics, but with emphasis on developing new methods and insights from data facilitating improvements to our operational data analytics capability.
Work locations: Birmingham, Bristol, Leeds, Swindon, Nottingham or Manchester
Hybrid working arrangement - 2 days per week in the officeKey Responsibilities:

Support the delivery of GPA's Information & Data Strategy and wider reporting requirements.
Support the delivery of reporting & dashboard business KPI's, providing more focussed support to business critical dashboards and reporting
Responsible for leading a team of developers and monitoring their daily duties to ensure a high performing team, supporting and delivering against business outcomes.
Leading the data analytics team in design, development, testing and release to its intended audience.
Support the team with business engagement, hosting working group sessions to provide updates to all levels of the business.
Collaborate across GPA at all levels to gather requirements and produce new dashboards that will aid in their daily working duties for the GPA.Profile

Person Specification / Key Skills Criteria & Qualifications:

As a data driven organisation, a data analytics lead is essential to assure the organisation can devise approaches and systems to 'make sense' of the large volumes of data present in the organisation
The data analytics and science lead ensures that the GPA:
Engages and liaises across GPA to ensure Business Intelligence requirements are captured and understood
Has fully documented methods and approaches to create BI products updated
Has reliable and accurate Business Intelligence applications deployed as required by the business
Oversee the investigation / development of new methods for data analysis such as AI

Essential criteria:

Power BI, Azure, Redshift, Databases, Power Platform, Dev Ops, SQL
Design and development of Power BI artefacts and environments
Numerical analysis methods
Stakeholder management and consensus building
Working in an Agile development environment
Managing a team of software developers / engineers
A computer/analytics University degree

Desirable criteria:

Work prioritisation and scheduling to time and budget
People training & development
Using Agile development environments such as JIRA
Microsoft Accreditation for Data Analytics (DA-100)
Gold Standard: IT & Data Management - CITP / CsyPJob Offer

28.9% Government Pension Scheme + Excellent Benefits

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.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.