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- Tasks: Lead product analytics for our Zable app, driving insights and shaping user experience.
- Company: Join a top fintech company with a focus on innovation and inclusivity.
- Benefits: Competitive salary, equity options, remote work flexibility, and health insurance.
- Why this job: Make a real impact on a product used by over 1 million customers.
- Qualifications: 5+ years in data analytics, strong SQL and Python skills, and A/B testing expertise.
- Other info: Enjoy fresh lunches, a collaborative environment, and excellent career growth opportunities.
The predicted salary is between 70000 - 90000 £ per year.
We are looking for an experienced Lead Product Data Scientist to drive product analytics across our rapidly evolving multi-product app. In this role, you will play a pivotal part in uncovering insights that shape and accelerate our Zable app, which is used by over 1 million customers on iOS and Android. This is a high-impact role where your insights will directly shape product strategy and accelerate our core user experience.
You will serve as the primary analytical voice for our Zable app, driving the entire experimentation lifecycle, influencing the decision relating to user experience, and shaping critical business decisions. Beyond individual contribution, you will be instrumental in establishing analytical best practices, and acting as a key strategic thought partner to Product, Growth, and Engineering leadership.
What You’ll Do
- Drive Product Analytics
- Be the dedicated analytical leader for the Zable app, deeply understanding user behavior and engagement drivers to identify high-impact opportunities.
- Develop and maintain key product metrics, dashboards, and reporting frameworks that provide visibility into user behavior, overall app health, and business performance.
- Conduct deep-dive analyses into user behaviour, segmentation, and lifecycle patterns to identify growth opportunities and friction points.
- Apply data science techniques to build predictive models for user behavior, churn risk, and uplift modeling to inform proactive product decisions.
- Drive Experimentation & Testing
- Own the end-to-end A/B testing process, including experimental design, execution, analysis and recommendations.
- Establish experimentation standards and best practices, including test design, statistical rigour, and result interpretation.
- Shape Strategy & Decision-Making
- Challenge assumptions and provide data-driven perspectives that shape strategic discussions and roadmap planning.
- Proactively partner with product managers, analysts and engineers to embed data into the daily decision-making flow and translate complex findings into clear business recommendations.
- Establish Analytical Excellence
- Define and champion analytics best practices, standards, and methodologies within the growth analytics team.
What We’re Looking For
- Core Qualifications
- 5+ years of experience in data analytics, ideally within a product-led or high-growth tech environment.
- Hands-on experience with dbt and familiarity with data modelling best practices.
- High proficiency in SQL and strong proficiency in data analysis in Python.
- Demonstrates strong statistical rigour, applying appropriate methods to ensure robust, reliable insights.
- Highly skilled in experimentation frameworks, including A/B testing, hypothesis testing, and causal inference.
- Experience building metrics, dashboards and reporting infrastructure.
- Demonstrated ability to turn ambiguous problems into structured and data-driven insights.
- Excellent communication skills with experience influencing cross-functional stakeholders and product leaders.
- Nice to Haves
- Experience in product analytics.
- Experience in fintech or financial services products.
Interview process
- Screening call with a recruiter.
- Take home task.
- Task Debrief.
- Case study Interview.
- Final Interviews.
The opportunity to scale up one of the world’s most successful fintech companies. Best-in-class compensation, including equity. You can work from home every Monday and Friday if you wish - on the other days we all come together IRL to be together, build and exchange ideas. Our in-house chefs prepare fresh, healthy lunches in the office every Tuesday-Thursday. We care for our Lendies’ well-being both physically and mentally, so we offer coverage when it comes to private health insurance. We’re an equal opportunity employer and are keen to make Lendable the most inclusive and open workspace in London.
Lead Product Data Scientist employer: Lendable Ltd
Contact Detail:
Lendable Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Product Data Scientist
✨Tip Number 1
Get to know the company inside out! Research Zable's app, its features, and user feedback. This way, when you chat with us, you can show off your knowledge and passion for what we do.
✨Tip Number 2
Practice your storytelling skills! We want to hear how your past experiences have shaped your analytical approach. Be ready to share specific examples of how you've driven product analytics and influenced decisions.
✨Tip Number 3
Prepare for the A/B testing deep dive! Brush up on your experimentation frameworks and be ready to discuss how you've designed and executed tests in the past. We love data-driven insights that lead to impactful changes.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows us you're genuinely interested in joining our team at Zable.
We think you need these skills to ace Lead Product Data Scientist
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Lead Product Data Scientist role. Highlight your experience in product analytics and data science techniques that align with what we’re looking for. This shows us you’re genuinely interested and have the right skills!
Showcase Your Impact: When detailing your past experiences, focus on the impact you’ve made in previous roles. Use metrics and specific examples to illustrate how your insights shaped product strategies or improved user experiences. We love seeing how you’ve driven results!
Be Clear and Concise: Keep your application clear and to the point. Avoid jargon unless it’s relevant to the role. We appreciate straightforward communication, so make sure your key achievements and skills shine through without unnecessary fluff.
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 gives you a chance to explore more about our company culture and values!
How to prepare for a job interview at Lendable Ltd
✨Know Your Data Inside Out
As a Lead Product Data Scientist, you’ll need to demonstrate a deep understanding of user behaviour and engagement drivers. Before the interview, dive into any available data on the Zable app. Familiarise yourself with key metrics and be ready to discuss how you would approach analysing user behaviour and identifying growth opportunities.
✨Master the Experimentation Process
Since you'll own the A/B testing process, brush up on your experimentation frameworks. Be prepared to discuss your experience with experimental design, execution, and analysis. Think of specific examples where your insights from testing led to impactful product decisions, and be ready to share these during the interview.
✨Communicate Clearly and Confidently
You’ll need to influence cross-functional stakeholders, so practice articulating complex data findings in a clear and concise manner. Prepare to explain how you’ve turned ambiguous problems into structured insights in the past. This will showcase your communication skills and ability to translate data into actionable business recommendations.
✨Showcase Your Analytical Excellence
Highlight your experience in establishing analytical best practices. Be ready to discuss how you've defined standards and methodologies in previous roles. This is your chance to demonstrate not just your technical skills, but also your leadership in driving analytical excellence within a team.