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For Companies At a Glance
- Tasks: Transform complex data into actionable insights that drive business decisions.
- Company: Join a fast-paced fintech startup with a collaborative culture.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a tangible impact on high-stakes projects influencing company growth.
- Qualifications: Strong analytical skills and experience with SQL, Python, or R.
- Other info: Work closely with senior leadership and diverse teams in a dynamic environment.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Location: Hybrid – 4 days onsite (Victoria, London) & 1 day remote
About the Role
I'm working with a Fintech who are looking for a Data Analyst / Scientist with a strong analytical and quantitative background to join a growing data function within a fast-paced, collaborative startup environment. The business already has a Data Scientist in place, but increasing data demands mean there is now a need to add analytical capacity, reduce key-person risk, and embed data more deeply across the business. This role prioritises business insights and decision support over advanced ML, while requiring strong mathematical, statistical, or quantitative skills to inform commercial decisions. You’ll be working in a collaborative, fast-paced environment where data drives decision-making across risk, fraud, customer insights, efficiency initiatives, and co-brand partnerships. This is an excellent opportunity for someone with strong technical, analytical, and quantitative skills, who is eager to grow with the business and make a tangible impact. You’ll turn complex data into actionable insights that influence commercial and operational decisions, working closely with internal teams and external partners.
Responsibilities
- Work alongside an existing Data Scientist to support analytics and decision‑making across the business
- Execute SQL‑driven analysis to support decision‑making across risk, fraud, bad debt, and efficiency initiatives
- Support initiatives across risk, fraud detection, and bad debt reduction
- Act as a data partner to internal teams and external co‑brand partners
- Prioritise incoming data requests and improve efficiency
- Apply quantitative and statistical skills to solve commercial and operational problems
- Translate business questions into analytical solutions using SQL, Python, or R, providing actionable insights
- Help build scalable dashboards and reporting to enable self‑serve analytics
- Collaborate closely with data engineers to understand and improve data pipelines, ensuring data quality and accessibility
- Present insights to senior leadership
- Partner with finance, product, and operational teams to deliver data‑driven recommendations impacting revenue, cost, and efficiency
- Balance analytical problem‑solving with technical rigor, without requiring advanced ML or research experience
- Experience with BI and visualisation tools (Metabase, QuickSight)
- Exposure to Redshift, Snowflake, MongoDB, or Excel
- Fintech or startup experience
- Previous experience in client‑facing or stakeholder‑facing roles
Profile Fit
- Technically strong but analysis‑heavy and commercially curious
- Comfortable partnering with the business to deliver actionable insights
- Motivated by practical impact over theoretical complexity
- Confident influencing decision‑making through data‑driven recommendations
- Confident in conversations with senior stakeholders and peers
- Enjoys working in an in‑person, highly collaborative environment
Why This Role Is Exciting
- Join a small but growing data team with exposure to multiple business areas
- Opportunity to help shape and evolve the data function from support to strategic partner
- High exposure to senior leadership and commercial decision‑making
- Work on high‑impact projects that directly influence company growth, revenue, and efficiency
Data Analyst employer: Propel
Contact Detail:
Propel Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even casual coffee chats. Building relationships can lead to job opportunities that aren’t even advertised.
✨Show Off Your Skills
Create a portfolio showcasing your analytical projects. Use platforms like GitHub to share your SQL queries or visualisations. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Ace the Interview
Prepare for common data analyst interview questions, but also be ready to discuss how you've used data to drive decisions in past roles. Practice explaining your thought process clearly and confidently!
✨Apply Through Our Website
Don’t forget to check out our website for job openings! Applying directly through us not only shows your interest but also helps you stand out as a candidate who’s keen on joining our team.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Analyst role. Highlight your analytical and quantitative background, and don’t forget to mention any relevant tools like SQL or Python that you’ve used.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how your previous experiences can help us make data-driven decisions. Keep it concise but impactful!
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex data problems in the past. We want to see your analytical thinking in action, so don’t hold back on sharing those success stories!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Propel
✨Know Your Data Tools
Make sure you're familiar with SQL, Python, and R, as these are crucial for the role. Brush up on your skills and be ready to discuss how you've used these tools in past projects to derive insights.
✨Understand the Business Context
Research the fintech industry and the specific company you're interviewing with. Be prepared to discuss how data can drive decision-making in areas like risk and fraud detection, and think of examples where you've made a tangible impact in similar situations.
✨Prepare for Scenario Questions
Expect questions that ask you to solve real-world problems using data. Practice articulating your thought process clearly, showing how you would translate business questions into analytical solutions and present actionable insights.
✨Show Your Collaborative Spirit
This role emphasises teamwork, so be ready to share experiences where you've successfully partnered with internal teams or stakeholders. Highlight your ability to communicate complex data findings in an understandable way to non-technical audiences.