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- Tasks: Drive product strategy using data insights and collaborate with cross-functional teams.
- Company: Join a mission-driven tech company transforming consumer experiences.
- Benefits: Up to £85,000 salary, hybrid work, 25 days holiday plus birthday off.
- Why this job: Shape the future of data in a greenfield opportunity with real impact.
- Qualifications: Strong SQL and Python skills, experience in consumer tech or product analytics.
- Other info: Dynamic team culture with excellent learning and development opportunities.
The predicted salary is between 72000 - 85000 £ per year.
A discount platform serving 4M+ members across the UK with access to 15,000+ partner discounts. £72M revenue, £375M member savings, expanding globally. 250+ employees with leadership from top consumer tech companies (Depop, Skyscanner, Monzo, Just Eat). Mission-driven culture rewarding key workers. Data-driven decision making at the core.
Join the Data team as a Product Data Scientist working with Product and Business stakeholders to drive strategy through insight. Similar to Monzo's Product Data Science model - embedded within product teams, solving problems, informing decisions, guiding strategy. Reports to Director of Data, works alongside Product Data Analyst, Analytics Engineers, and Data Scientists.
What you’ll do:
- Use quantitative analysis and data storytelling to uncover user behaviour and inform product strategy
- Design and support experiments, generate hypotheses, foster continuous learning
- Define and align key metrics with stakeholders, ensure data accuracy across teams
- Build self-serve dashboards and data tools for quick access to core insights
- Conduct deep-dive analyses supporting strategic initiatives with clear recommendations
- Maintain central Insights Hub with documented reports and metric definitions
- Collaborate cross-functionally to close data gaps and foster strong relationships
- Champion unified data approach and stay current on analytics best practices
- Own problem spaces end-to-end, not just analysis - deliver outcomes
Greenfield opportunity with full ownership, autonomy to identify right questions, design experiments, and drive revenue-impacting decisions.
Tech Stack:
- Database: SQL (essential — must be strong)
- Transformation: dbt (comfortable using, not expert-level required)
- Languages: Python (for exploratory analysis, notebooks)
- Version Control: Git
- Analytics: GA, product analytics tools, web tracking
- Some exposure to basic ML elements (exploratory modelling)
What you need:
- Extensive experience working with data in an analytical fashion in a digitally native tech environment
- Consumer tech or product experience is a must - worked with product teams and business stakeholders
- Strong SQL skills - work independently creating complex queries
- Hands-on Python (or R) experience for exploratory analysis
- Experience with dbt, Lightdash, Looker, or Tableau
- Product analytics background - experimentation, A/B testing, user behaviour analysis
- Statistical rigor - appropriately skeptical, understand how to design experiments that isolate real effects
- Strong data storytelling and presentation skills - ability to present convincing, data-led arguments to stakeholders at all levels
- Ability to translate business problems into analytical tasks and communicate insights effectively
- Product-minded approach - care about the "why" behind analyses, can push back constructively
- Self-starter with strong curiosity to understand user behaviour
- Detail-oriented problem solver who can balance rigor with speed
- Team player who is both highly collaborative and individually capable
- Ability to manage your own development and identify opportunities for improvement
- Can deliver and execute, not just analyze - pragmatic problem-solver
Nice to have:
- Experience in membership, subscription, or marketplace businesses
- Exposure to fintech or consumer tech scale-ups
- Background in companies like Monzo, Revolut, Deliveroo, Gousto, or similar product-led consumer tech
- Familiarity with modern data stack tools
- Understanding of affiliate networks or commission tracking
What’s on offer:
- Salary: Up to £85,000
- Location: London (Holborn) or Leicestershire - hybrid 2 days/week. London-based: travel to Leicestershire once/month
- Impact: Greenfield opportunity - shape data function, build from ground up
- Strategic: Drive strategy and product decisions, not just reporting
- Mission-Driven: Tech for good - support key workers
- Holiday: 25 days + birthday off + buy/sell scheme (up to 5 days)
- Bonus: Company bonus scheme
- Health: BUPA medical insurance (covers pre-existing conditions) + healthcare cashback
- Benefits: Membership with 15,000+ discounts, pension, enhanced parental leave, EAP
- Perks: Free parking & EV charging at HQ, onsite gym, modern offices, social events, strong L&D culture
Interview Process:
- 45 minute Teams with Director of Data - work experience, current situation, more about the role
- 1 hour Teams with Director of Data + Data Team member - case study presented during interview (two prompts on experimentation, product thinking, structured problem solving)
- 1 hour in-person meeting with 10 minute presentation on past experience
- Potential short Teams with CPO (TBC)
Timeline: 3-4 weeks
How to apply: Send your CV to Mohammed Buhariwala at Harnham.
Product Data Scientist in Leicester employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Product Data Scientist in Leicester
✨Tip Number 1
Get your networking game on! Reach out to people in the industry, especially those who work at companies you're interested in. A friendly chat can open doors and give you insider info that could help you stand out.
✨Tip Number 2
Prepare for those interviews like a pro! Research the company, understand their products, and think about how your skills can solve their problems. Practise common interview questions and have your own questions ready to show your interest.
✨Tip Number 3
Show off your data storytelling skills! During interviews, use examples from your past work to illustrate how you've used data to drive decisions. Make it relatable and engaging – remember, they want to see how you think!
✨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, we love seeing candidates who are proactive and take the initiative to connect with us directly.
We think you need these skills to ace Product Data Scientist in Leicester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Product Data Scientist role. Highlight your experience with SQL, Python, and any product analytics you've done. We want to see how your skills align with what we're looking for!
Showcase Your Data Storytelling: We love a good data story! When you write your application, include examples of how you've used data to inform decisions or strategies in previous roles. This will help us see your analytical mindset in action.
Be Clear and Concise: Keep your application clear and to the point. Use bullet points where possible to make it easy for us to read through your experiences and skills. We appreciate a well-structured application!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Harnham
✨Know Your Data Tools
Make sure you're well-versed in SQL and Python, as these are essential for the role. Brush up on your skills by practising complex queries and exploratory analysis. Familiarity with dbt and data visualisation tools like Looker or Tableau will also give you an edge.
✨Understand the Product Mindset
Get into the mindset of a product data scientist. Be prepared to discuss how you can translate business problems into analytical tasks. Think about how your analyses can drive product strategy and user behaviour insights, and be ready to share examples from your past experience.
✨Prepare for Case Studies
Since the interview includes case studies on experimentation and structured problem-solving, practice presenting your thought process clearly. Use real-world scenarios to demonstrate your ability to design experiments and analyse results effectively.
✨Show Your Collaborative Spirit
This role requires strong collaboration with cross-functional teams. Be ready to discuss how you've worked with product teams and stakeholders in the past. Highlight your ability to foster relationships and champion a unified data approach, as this will resonate well with the interviewers.