Data Analyst - Financial Services
Utility Warehouse are seeking an experienced Data Analyst to play a key role in answering fundamental and invaluable questions within our Financial Services business. Your analysis and modelling will inform our strategic decision making, product development, and play a vital role in how we continue to grow our Financial Services proposition.
We're a supplier of home services (Energy, Telephony, Insurance, Broadband & Prepaid Cards) with around 2% of the UK market, a unique business model built on unparalleled word of mouth marketing, and a huge potential to grow.
Having been around for more than 20 years, our strong financial position allows us to invest heavily in technology that helps us innovate, compete, and deliver major growth. We’re building user-focused, data-driven, agile, autonomous teams and have the backing of the board to achieve big results.
What you will do:
As our Financial Services Data Analyst, you will be responsible for providing the information and insight necessary to enable data led decisions across both our Insurance and Cashback Card teams. That includes designing and answering specific hypotheses and experiments for product development, creating and maintaining reports, dashboards and KPIs that are used by product teams and senior management, as well as formulating the right metrics to help us accurately understand how we’re doing. On top of that, you’ll also be working on domain modelling - blending data from our portfolio of services - to spot product opportunities, and using automation where relevant to help your analysis scale.
In your first 3 months we’ll be expecting you to focus on understanding, documenting and curating information needs within the Financial Services teams, as well as reviewing existing assets from across the business, to formulate and then execute an analytics roadmap in partnership with the product teams, our Data Platform team and data scientists. This will help you to become the subject matter expert and first point of contact for our growing Financial Services data needs.
To do that, you’ll be working in and across a number of agile teams, ensuring analytics is a first class citizen and not just represented on the product team’s roadmap but delivering real value. We’ll expect you to work directly with engineers to ensure your technical data requirements are understood so you get the data you need, but also to empower the teams to get the most from your data.
We work across diverse data sets and use a variety of different tools, technologies and techniques. We’ll expect you to do this too, and you’ll help us build on our core suite of data assets and services that power in-depth insight.
The successful candidate will be a data evangelist, possessing curiosity and an inquisitive attitude, and preferably with experience of building and articulating an analytics backlog. Technically, you will need to be comfortable with data manipulation, processing and modelling. This role is an excellent opportunity for a candidate seeking the opportunity to drive themselves with their own enthusiasm for data.
You will need:
- A passion for data analytics and reporting
- Solid experience in SQL
- Experience working with and manipulating numerical and time series data
- Knowledge of relational and non-relational data sources
- Experience using Python for data analytics
- Familiarity with fundamental statistical concepts
- Basic data visualisation and storytelling skills
- Strong stakeholder management experience, It is imperative being able to set expectations on what is and is not possible to do with the data available
- Experience creating and curating a backlog of work to form a roadmap
- To be a self-starter, bringing your own creativity, enthusiasm and real world problem-solving a rapidly changing business
Bonus points will be given for the following although not essential...
- Use of cloud analytics tools and platforms e.g. Looker, BigQuery
- Use of cloud infrastructure providers e.g. AWS, GCP
- Use and knowledge of version control technologies e.g. git
- Exposure to ETL tools is a plus