At a Glance
- Tasks: Analyse operational data to uncover insights and improve efficiency using AI tools.
- Company: Join a pioneering AI-enabled PropTech startup transforming property services.
- Benefits: Competitive salary, bonuses, share options, and a hybrid work model.
- Other info: Be part of a dynamic team driving innovation in the property sector.
- Why this job: Make a real impact in a fast-paced environment with visible results.
- Qualifications: Strong analytical skills, experience with SQL, and a knack for data quality assurance.
The predicted salary is between 75000 - 75000 £ per year.
This is the UK's first AI-enabled roll-up of property service companies. Backed by leading VCs and founded by the team behind one of the UK's largest digital property managers, the business acquires excellent owner-operated companies and transforms them into a modern, technology-enabled group using AI.
Every business they acquire brings its own data - different systems, different standards, different levels of rigour. The centre of gravity is insight - finding patterns in operational data, understanding what they mean for how a business runs, and communicating that clearly to operators and leadership who are not data specialists.
- Analysis and Insight – Explore operational data across acquired businesses to find patterns, inefficiencies, and improvement opportunities.
- Put AI tooling to work on analysis, reconciliation, and anomaly-spotting at scale.
- Inbound Data Quality – Own QA on inbound data from newly acquired companies - profiling, reconciliation, validation against source, anomaly detection.
- Develop the instinct for where data is wrong before it reaches our systems, not after.
- Use AI tooling to strengthen and accelerate validation.
- Internal Data Products – Partner with engineering and internal users to shape data products - defining metrics, clarifying requirements, validating that outputs are correct and useful.
- Be the analytical voice in product conversations, translating operational reality into data model requirements.
Contribute to transformation logic, source-to-target mappings, and data preparation alongside the engineering team.
- Strong analytical background - analyst, BI, or data science roles where insight drove decisions, not just dashboards.
- SQL and spreadsheets at a high level; comfortable interrogating and reconciling data rather than taking it on trust.
- Experience doing real data QA - profiling, validation, reconciliation, anomaly detection - with an instinct for where data goes wrong.
- Resourceful with AI tooling - knows how to use LLMs to accelerate analysis and validation work.
- Some ETL exposure: transformation logic, mappings, data preparation - you don't need to own pipelines, but you need to understand them.
- This role is not right for pure data engineers with no analytical instinct, analysts who take data at face value, or people who need a fully-defined brief before they can start.
A pivotal early hire in the data function of one of the UK's most ambitious AI-PropTech startups.
- Real breadth - working across multiple businesses, asset types and operational challenges simultaneously.
- Competitive salary, bonus and share options.
- A company where the work you do is visible and the impact is immediate.
Senior Data Analyst - PropTech Startup in City of London employer: Urban Digital Recruitment Ltd
Join a pioneering PropTech startup that is revolutionising the property services industry with AI-driven insights. Located in London, this hybrid role offers a competitive salary, bonus, and share options, alongside a vibrant work culture that values innovation and collaboration. As a Senior Data Analyst, you'll have the opportunity to make a tangible impact across multiple businesses while enjoying excellent growth prospects in a dynamic environment backed by leading VCs.
Contact Details:
Urban Digital Recruitment Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst - PropTech Startup in City of London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Urban Digital Recruitment Ltd.
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We think you need these skills to ace Senior Data Analyst - PropTech Startup in City of London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Urban Digital Recruitment Ltd, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Urban Digital Recruitment Ltd. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Urban Digital Recruitment Ltd
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Urban Digital Recruitment Ltd!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
