At a Glance
- Tasks: Transform data into insights that drive impactful decisions and support business growth.
- Company: Join Smart, a pioneering fintech company revolutionising retirement and savings.
- Benefits: Enjoy 25 days holiday, professional development budget, and extensive healthcare.
- Other info: Collaborative culture with opportunities for personal and professional growth.
- Why this job: Be part of a dynamic team making a real difference in financial wellbeing.
- Qualifications: 3+ years in data analysis, strong SQL skills, and a passion for storytelling with data.
The predicted salary is between 40000 - 50000 £ per year.
At Smart, our mission is to transform retirement, savings and financial wellbeing, across all generations, around the world.
The Role
As part of the Data Analytics team, you will work closely with stakeholders to translate business challenges into data problems, delivering high‑quality and clearly articulated analysis, reporting, and data‑driven insights that support effective decision‑making. We are a small team with big ambitions. We are building the foundations to enable our vision of maximising the value that our extensive dataset and modern data stack can generate for the business. Because we support the entire business, our data is varied and complex. As such, we are seeking a self‑starter who is comfortable navigating ambiguity and independently finding solutions within a fast‑paced environment. If you match our ambitions, are passionate about creating value from data, and want to help drive the evolution of our data capabilities, then we would love to hear from you.
What You Will Do
- Stakeholder Partnership & Communication
- Define requirements: Partner with stakeholders across the company to translate business questions into clear analytics requirements and identify the right data points.
- Data translation & storytelling: Explain analytical outputs and insights to stakeholders in clear, non‑technical terms and, as required, build a narrative to support effective decision‑making.
- Drive data literacy: Support initiatives that enable stakeholders to self‑serve data more effectively.
- Analytics & Business Intelligence
- Build BI solutions: Design, build, and maintain reports and dashboards (primarily using Tableau) used across the organisation, including Board‑level KPI reporting.
- Data analysis & insights: Manipulate and analyse complex data to answer business questions and identify trends, insights, and opportunities.
- Data Modeling & Quality Assurance
- Build robust data models: Develop and maintain optimised and reliable solutions in our data warehouse (Redshift) using tools like dbt, collaborating closely with Data Engineering where required.
- Ensure trust & accuracy: Maintain data quality and reporting reliability, manage the impact of upstream changes, and support business‑critical processes with direct regulatory or customer impact.
- Peer review: Participate in code reviews and collaborative QA to validate the accuracy and value of our analytical output.
- Continuous Improvement & Team Culture
- Automate & optimise: Identify opportunities to improve efficiency through automation, better data processes and the responsible use of AI.
- Be an active team player: Contribute your ideas to team discussions, retrospectives, and future planning to continuously improve how we work together and support the business.
Who We Are Looking For
The skills, experience, and aptitudes we are looking for are listed below but please don’t be discouraged from applying if you don’t meet every single one of these criteria – having a ‘can do’ attitude is sometimes more important than being able to tick every box:
- Experience & Attributes
- Proven track record: 3+ years of experience in data analysis, with a focus on data manipulation, reporting and insight analytics.
- Stakeholder partnership: A proven ability to work with stakeholders to deeply understand business problems, translate requirements into effective analytics solutions, and advise on best approaches.
- Data storytelling & coaching: An effective technical communicator who can translate complex data for non‑technical audiences and actively coach stakeholders to enhance overall data maturity.
- Analytical curiosity: Inquisitive by nature, with sharp attention to detail and a natural drive to look beyond the surface numbers to uncover actionable insights.
- Ambitious and agile learner: A fast, curious learner who is eager to independently explore and pick up new datasets, technologies and methodologies to innovate with purpose.
- Organised & adaptable: Highly organised with the ability to manage multiple concurrent tasks.
- Collaborative team player: A reliable team player with a “team‑first” mindset who thrives in a highly collaborative and supportive environment.
- Financial Services/Pensions experience (Desirable): Experience within financial services is desirable; exposure to the pensions industry is a plus.
- Technical Skills
- Advanced SQL (Essential): Extensive experience of writing, troubleshooting, and optimising complex queries.
- BI & Data Visualisation (Essential – Tableau Preferred): Strong experience building impactful dashboards and reports in a modern BI tool, with a preference for Tableau.
- dbt (Desirable): Experience with dbt for data modelling, transformation, and managing the analytics layer.
- Python (Desirable): Experience using Python for data manipulation, advanced analytics or automation.
- Git / GitHub (Desirable): experience using version control for managing code, collaborating with others, and reviewing changes.
Who We Are
We work in partnerships with governments and financial institutions in the UK and internationally. Our cloud‑native digital platform is revolutionising how people around the world think about, and save for, their retirement. At heart, we’re a financial technology business. What we do is all about innovation, and using the power of digital change to put the customer first. Our Engineers will tell you that working at Smart gives you the opportunity to play your part in developing world‑class technological solutions, working with – and learning from – like‑minded people. You’ll also find that, across our business, our colleagues love Smart’s culture, and how what we do means better financial outcomes for savers. That feels worthwhile, and it means that what we do, collectively, goes way beyond the nine to five of a typical working day.
Benefits
- 25 days’ holiday per year, increasing with length of service.
- £500 annual training budget to spend on your professional development.
- Extensive private healthcare, including dental, eyecare and EAP.
- Enhanced sick leave (three months’ pay per year).
- Enhanced maternity and paternity (maternity – 6 months fully paid, paternity – 3 weeks fully paid).
- Death in service insurance cover.
- Fully‑paid five‑week sabbatical after five years of employment.
- In‑office wellbeing, such as manicures, massages and barbers.
- Smart employees also enjoy a 50% discount on orders from our sister company Arena Flowers, Britain's most ethical florist.
At Smart, we are committed to creating an inclusive and equitable workplace where everyone feels valued, respected, and empowered to do their best work. We believe that diverse perspectives help us lead the way in transforming retirement, savings and financial wellbeing. We welcome differences in background, experience, thinking, and identity, and we recognise that innovation is strongest when it is built on inclusion and fairness. We encourage applications from people of all backgrounds and experiences and do not discriminate on the basis of any protected characteristic. If you require any reasonable adjustments during the recruitment process or in the workplace, we encourage you to let us know - we are committed to supporting you. We think Smart is an awesome place to work. If it sounds like somewhere you’d like to work, too, and if you’re ready to play your part in our continued success in the future, then naturally we’d love to meet you.
Data Analyst employer: Smart Pension
At Smart, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our commitment to employee growth is evident through our generous benefits, including a £500 annual training budget, extensive private healthcare, and a fully-paid five-week sabbatical after five years of service. Located in a dynamic environment, we empower our Data Analysts to thrive by providing opportunities to work with cutting-edge technology while making a meaningful impact on financial wellbeing across generations.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Smart Pension!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Analyst at Smart Pension.
✨Leverage Professional Networks
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 Smart Pension.
✨Apply Directly through Our Website
When you find a suitable opening like Data Analyst at Smart Pension, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Analyst
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 Smart Pension, 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 Smart Pension. 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 Smart Pension
✨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 Smart Pension!
✨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.