At a Glance
- Tasks: Unlock actionable insights from data to drive product strategy and customer empathy.
- Company: Join a forward-thinking team at Fin, focused on data-driven decision-making.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on AI tools and automation.
- Why this job: Make a real impact by shaping products that millions use daily.
- Qualifications: 5+ years in data science, strong SQL skills, and experience with product teams.
The predicted salary is between 60000 - 80000 £ per year.
The Research, Analytics & Data Science (RAD) team at Fin uses data and insights to drive evidence-based decision-making. We are a team of data scientists and product researchers who use data to unlock actionable insights about our customers, products, and business. We generate insights that build customer empathy, drive product strategy, and shape products that deliver real value. If you get excited about asking the right questions, exploring patterns in data, and turning insights into action, this role is for you.
Data Scientists in RAD partner with teams across R&D to help Fin make sense of our users, products, and business, using metrics, data, and analysis. This role will enable you to drive key data projects that directly impact our customers and millions of end users who communicate via our messaging platform daily.
What will I be doing?
- You’ll partner with product teams to help them identify important questions and answer those questions with data.
- You’ll work closely with product managers, designers, and engineers to develop key product success metrics, set targets, measure results and outcomes, and size opportunities.
- You’ll design, build, and update end-to-end data pipelines, working closely with stakeholders to drive the collection of new data and the refinement of existing data sources and tables.
- You’ll partner closely with product researchers to build a holistic understanding of our customers, products, and business.
- You’ll influence our product roadmap and product strategy through exploratory analysis and quantitative research.
- Increasingly, you will also:
- Use AI-assisted tools (e.g. Claude Code, Cursor) to accelerate analysis, coding, and insight generation.
- Identify opportunities to automate your own workflows and reduce time spent on repetitive tasks.
- Build scalable data products (dashboards, models, internal tools) that enable stakeholders to self-serve insights.
- Help teams interact more directly with data (e.g. through better abstractions, semantic layers, or AI-powered interfaces).
- Raise the bar for how AI is used within RAD - sharing patterns, workflows, and best practices.
- Craft clear, compelling data stories and communicate recommendations across R&D and the broader company.
- Contribute to and shape core RAD foundations, improving how the team operates.
What skills do I need?
- 5+ years experience working with data to solve problems and drive evidence-based decisions.
- Strong SQL skills and solid grounding in statistics.
- Experience working closely with product teams.
- Proven track record of delivering actionable insights that drive measurable impact with minimal supervision.
- Strong product intuition, business acumen, and ability to connect analysis to strategy.
- Excellent communication skills (technical and non-technical), with a focus on driving decisions and outcomes.
- Strong ownership, curiosity, and growth mindset.
- Experience with a scientific computing language (e.g. Python).
And increasingly important:
- Ability to effectively use AI tools (e.g. Claude Code, Cursor) to accelerate and improve your work.
- A mindset of automation and leverage - looking for ways to scale your impact beyond one-off analyses.
- Comfort working in ambiguous, fast-evolving environments where tools and workflows are rapidly changing.
Bonus skills & attributes
- Experience with data modeling and ETL pipelines (especially dbt).
- Experience building internal tools, data products, or self-serve analytics capabilities.
- Experience leveraging AI across the data workflow - from ideation and coding to analysis and communication.
Senior Data Scientist employer: Fin
At Fin, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our Senior Data Scientists play a crucial role in shaping product strategy through data-driven insights, while enjoying ample opportunities for professional growth and development. Located in a dynamic environment, we offer unique advantages such as access to cutting-edge AI tools and a commitment to employee well-being, making Fin a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees at Fin or similar companies on LinkedIn. Ask them about their experiences and any tips they might have for landing a role in the RAD team. Personal connections can make all the difference!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those that highlight your ability to turn insights into action. This will give you an edge during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the interview by brushing up on your SQL and statistics knowledge. Be ready to discuss how you've used data to drive decisions in past roles. Practice explaining complex concepts in simple terms – it’s all about clear communication!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team at Fin.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior Data Scientist. Highlight your experience with data, SQL skills, and any projects where you've driven evidence-based decisions. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you're excited about this opportunity. Share specific examples of how you've used data to influence product strategy or drive insights. Let your passion for data science shine through!
Showcase Your Communication Skills:Since you'll be working closely with product teams, it's crucial to demonstrate your ability to communicate complex data insights clearly. Use your application to show us how you've effectively shared recommendations in past roles.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you're keen on joining the StudySmarter team!
How to prepare for a job interview at Fin
✨Know Your Data Inside Out
Before the interview, dive deep into your past projects involving data analysis. Be ready to discuss specific examples where you used SQL or Python to solve complex problems. Highlight how your insights drove decisions and impacted product strategy.
✨Showcase Your Collaboration Skills
Since this role involves working closely with product teams, prepare to share experiences where you partnered with product managers, designers, or engineers. Emphasise how you identified key questions and contributed to building success metrics that shaped product outcomes.
✨Demonstrate Your AI Savvy
Familiarise yourself with AI-assisted tools like Claude Code or Cursor. Be prepared to discuss how you've used these tools in your previous roles to enhance your analysis or automate workflows. This will show your adaptability and forward-thinking approach.
✨Craft Compelling Data Stories
Practice explaining your data findings in a clear and engaging way. Think about how you can turn complex analyses into compelling narratives that resonate with both technical and non-technical audiences. This skill is crucial for influencing product strategy and communicating insights effectively.
