At a Glance
- Tasks: Lead data analysis projects, create dashboards, and deliver insights for impactful decision-making.
- Company: Join a leading non-profit tackling the UK’s affordable housing crisis with innovative financial solutions.
- Benefits: Enjoy a competitive pension scheme, private medical insurance, and generous annual leave.
- Other info: Collaborative culture with opportunities for professional growth and upskilling.
- Why this job: Make a real difference in social housing while developing your data skills in a supportive environment.
- Qualifications: 5+ years in data analysis, strong SQL, Python, and Power BI skills required.
The predicted salary is between 55000 - 65000 £ per year.
This non-profit within the financial services sector has been the UK’s leading affordable housing aggregator for more than three decades, providing innovative funding solutions for 149 housing associations across all four nations of the UK. They have amassed a near £8bn loan book to date and continue to expand their range of financial products to serve the needs of the social housing sector. My client has made significant contributions toward solving the UK’s affordable housing crisis, having funded 32,000+ homes under Affordable Housing Finance Plc (AHF), which oversaw the government’s initial Affordable Housing Guarantee Scheme. The aggregator launched Blend Funding Plc (Blend) in 2018 which has grown to provide committed facilities to 33 housing associations totalling over £1.9bn. In February 2025, the organisation announced the launch of a groundbreaking £150m partnership with the National Wealth Fund (NWF) to finance retrofitting of affordable homes alongside its new lending vehicle THFC Sustainable Finance Plc (TSF).
About Your Role
The Senior Data Analyst will lead the design, automation and delivery of high-quality data products that unlock actionable insight for internal teams and external clients. They will own the end-to-end analytics lifecycle – from architecting robust SQL data models and pipelines, through advanced Python- and VBA-driven analysis, to building sophisticated Power BI dashboards and executive-ready reporting. Operating at the intersection of data engineering, business intelligence and commercial strategy, the role will translate large, complex datasets into clear narratives that support decision-making, business development and market analysis, while standardising data across disparate systems to enable scalable, repeatable analytics solutions.
The role reports to the Senior Director, Strategy, who manages digital strategy, IT, marketing, brand, and communications for the organisation.
Key Responsibilities:
- Data Analysis & Modelling
- Maintain and query large datasets using advanced SQL techniques
- Design and develop complex relational SQL data models
- Perform comprehensive data analysis to identify trends and insights
- Create and maintain robust data pipelines for continuous data processing
- Data Visualisation & Reporting
- Build and deploy interactive Power BI dashboards providing real-time insights to stakeholders
- Design compelling data visualisations that translate complex datasets into actionable intelligence
- Develop executive-level reporting solutions for internal teams, Board papers and client presentations
- Client & Stakeholder Engagement
- Collaborate with cross-functional teams to understand business requirements and deliver tailored solutions
- Support business development activities through data-driven insights, customer and market analysis
- Present findings and recommendations to senior stakeholders, using clear storytelling to influence decisions and drive adoption of data products
- Data Integration
- Standardise data across disparate systems with varying structures to support consistent analytics, reporting and performance tracking
- Define and implement robust data validation, monitoring and documentation practices in line with good data governance principles
- Work closely with IT and business teams to improve data capture, data definitions and metadata, ensuring long-term integrity of core datasets
- Leadership & ways of working
- Lead analytics projects end-to-end, from scoping and prioritisation through to delivery, stakeholder sign-off and embedding into business processes
- Establish and champion best-practice standards for data modelling, visualisation, automation and quality across the organisation
- Coach and upskill colleagues to increase data literacy and self-serve capability, through training, documentation and pair-working
- Stay up to date with emerging tools, techniques and regulation relevant to data in financial services and housing, and proactively propose improvements to The Housing Finance Corporation’s data environment
Candidate Profile
- Experience
- 5+ years’ experience as a Data Analyst (or similar role) in a corporate environment
- Financial services, capital markets and/or affordable housing / real estate industry experience strongly preferred
- Proven track record of working with large, complex datasets to deliver insight that supports business decisions
- Experience leading multi-stakeholder analytics projects and engaging confidently with senior decision-makers
- Technical
- SQL: Advanced querying capabilities, including complex joins, stored procedures and performance optimisation
- Python & VBA: Strong programming skills including pandas, data manipulation libraries and proficient in Excel automation and macro development
- Power Automate & SharePoint: Proficient in automated ETL workflows, data sync flows with error handling, SharePoint list connectors, and Power BI/Power Apps integration for live refresh and database write-back.
- Power BI: Expert-level skills including:
- Advanced DAX formula writing and optimisation
- Complex data modelling and relationships
- Custom visualisations and dashboard design
- Row-level security implementation and access management
- Power Query for data transformation and integration
- Calculated columns and measures
- Performance tuning and optimisation
- Database & Development
- Experience designing and implementing relational data models and working with database development teams
- Understanding of and experience in implementing data governance principles
- Analytical & Communication
- Strong analytical thinking and structured problem-solving abilities, with a focus on business impact
- Excellent written and verbal communication skills, with the ability to translate technical concepts for non-technical stakeholders
- Detail-oriented with strong quality assurance practices
- Qualifications
- Degree in data science, statistics, mathematics, computer science, economics or another quantitative discipline (or equivalent professional experience).
- Postgraduate or professional qualification in analytics, data, finance or a related field (for example MSc Data Science, CFA, ACA, FRM, MBA) is advantageous.
Benefits
- Pension scheme: We’re committed to helping you plan for the future. Our contributory pension scheme enables you to invest in your retirement, with The client matching your contributions to help your savings grow faster.
- Private medical insurance: Your health matters to us. Through Bupa private medical cover, you’ll have access to prompt, high‑quality healthcare, giving you reassurance and support when you need it most.
- Health support: Everyday health costs can add up, so our SimplyHealth plan helps towards dental, optical and physiotherapy expenses, as well as a range of wellbeing treatments — supporting your health inside and out.
- Annual leave: Time away from work is essential for balance and wellbeing. You’ll receive 25 days’ annual leave, increasing by one day each year (up to 30 days), plus an additional wellbeing day to recharge and your birthday off to celebrate in your own way.
Senior Data Analyst in London employer: Praxis Digital
As a leading non-profit in the financial services sector, our organisation is dedicated to addressing the UK's affordable housing crisis while fostering a collaborative and innovative work culture. Employees enjoy a comprehensive benefits package, including a contributory pension scheme, private medical insurance, and generous annual leave, alongside opportunities for professional growth and development in a mission-driven environment. Located in London, we offer a dynamic workplace where your contributions directly impact communities across the UK.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst in London
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We think you need these skills to ace Senior Data Analyst in 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 Praxis Digital, 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 Praxis Digital. 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 Praxis Digital
✨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!
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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 Praxis Digital!
✨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.
