At a Glance
- Tasks: Analyse marketing data to drive insights and optimise campaigns.
- Company: Join a dynamic team focused on enhancing marketing effectiveness.
- Benefits: Enjoy a hybrid work model and flexible contract terms.
- Other info: Contract role for 3 months, starting ASAP.
- Why this job: Make a real impact by bridging technical and marketing analytics.
- Qualifications: Experience in marketing analytics, A/B testing, and strong SQL skills required.
Job Title: Mid–Senior Level Data Analyst (Finance & Data Science)
Location: Hybrid – 4 days onsite (Victoria, London) & 1 day remote
I'm working with an exciting fintech startup that is redefining travel and loyalty spending through innovative debit card solutions. The business is at a stage where data-driven insights are critical to growth , and they are seeking a mid-to-senior level Data Analyst to join their Finance & Data Science team.
This is a hands‑on role for someone who enjoys solving real-world business problems and turning complex data into actionable insights . You will work across finance, product, marketing, and operations to influence key decisions. Strong communication and presentation skills are essential, as you will regularly present findings to senior leadership and external partners.
Key Responsibilities
- Analyse large, complex datasets to uncover trends, patterns, and opportunities that impact revenue, cost, and operational efficiency.
- Partner with finance, product, operations, and marketing teams to deliver commercially-driven insights .
- Translate business questions into analytical solutions using SQL, Python, or R , providing actionable recommendations.
- Develop dashboards, reports, and visualisations using BI tools (Tableau, Power BI, Metabase, QuickSight) to enable teams to self-serve insights .
- Work with data engineers on data modelling and orchestration pipelines using DBT and Airflow .
- Present insights clearly to senior stakeholders and non-technical audiences using compelling data storytelling.
- Monitor and improve the performance of analytics solutions over time.
Required Skills & Experience
- Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or equivalent practical experience.
- 3+ years of experience in data analysis with strong commercial impact — able to influence business decisions.
- Strong knowledge and hands-on experience with data modelling and orchestration tools: DBT and Airflow.
- Proficiency in SQL, Python, R , and BI/visualisation tools (Tableau, Power BI, Metabase, QuickSight).
- Experience working with data warehouses (Snowflake, Redshift) and cloud platforms (AWS, GCP, Azure).
- Excellent communication and presentation skills , able to explain complex analyses to senior leadership and external stakeholders.
Preferred Skills
- Familiarity with fintech or start-up environments.
- Exposure to Agile or cross-functional team environments.
- Experience deploying or maintaining analytics solutions in production.
Why This Role Is Exciting
- Join a small but growing mid-to-senior level team , helping shape how data drives commercial decisions.
- High exposure to senior leadership and cross‑functional stakeholders.
- Work on high-impact projects that directly influence revenue, cost, and operational efficiency.
- Competitive salary, equity plan, private healthcare, and 25 days holiday.
If this sounds like you or someone you know then send your CV over to
#J-18808-Ljbffr
Senior Data Analyst in London employer: Propel
As a Performance Marketing Manager at one of the UK's fastest-growing consumer fintechs, you'll thrive in a dynamic and collaborative environment that values innovation and autonomy. With a focus on strategic growth and a commitment to employee development, this company offers meaningful opportunities for career advancement while ensuring a strong return on marketing investments. Join a team that celebrates success and is dedicated to driving customer growth in an exciting phase of expansion.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst in London
✨Get Involved in Data Science Meetups
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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 Propel, 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 Propel. 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 Propel
✨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 Propel!
✨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.
