Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Real Estate Data Analytics Manager

PwC
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

PGIM Public and Private Fixed Income | Associate/ Senior Associate, Quantitative Modeling and S[...]

Client Data Analyst, Real Estate

Data Analytics Lead – Private Credit/Asset Based Finance

Senior Data Analyst

the role

The Real Estate Analytics team prides itself on leading the way in how we gather and interpret data available within the business, working with teams across PwC to implement a best in class approach to providing analytical insights to our Firm's leadership.

You'll join our team mainly based in London but can be based near any of our offices.

This role is ideal for a data visualisation expert, with good people management attributes to lead the visualisation team of four.

What your days will look like:

This role, as a sub-team lead will be to provide guidance to those that report to you, to maintain a clear plan (demonstrated through Gantt Charts) of work to be delivered. You will be engaging with customers to understand their requirements and providing for those requests by producing reports and dashboards, both by yourself and by utilising the skillsets of the team.

Roles and responsibilities

Manage a small team of data analysts, overseeing and delegating tasks. Plan and record a delivery plan of activities Coach and mentor reportees, upskilling and guiding through a Personal Development Plan Engage with customers, gather requirements and manage the delivery of those requests

This role is for you if:

You possess people management experience, both for day to day activities and coaching through a Personal Development Plan. Can manage a programme of work, balancing resourcing, customer needs and delegating with authority You ideally have previous Real Estate (Workplace analytics) industry experience Have strong knowledge of tools such as Python, Power BI, Alteryx

What you'll receive from us:

No matter where you may be in your career or personal life, our are designed to add value and support, recognising and rewarding you fairly for your contributions. 

We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.


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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.