Data Analytics & Data Science Lead

Birmingham
3 days ago
Create job alert

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

Related Jobs

View all jobs

Data Analytics & Data Science Lead

Managing Consultant - Transport - Data Science (Basé à London)

Data Science Manager – Gen/AI & ML Projects

Data Science Manager – Gen/AI & ML Projects - Bristol

Head of Data Science | London Market

Lead Data Engineer

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 in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

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.