At a Glance
- Tasks: Lead product experimentation and drive strategy through data insights.
- Company: Join ZOE, a mission-driven company transforming health with advanced science.
- Benefits: Competitive salary, growth opportunities, and a supportive team culture.
- Why this job: Make a real impact on health outcomes using cutting-edge data science.
- Qualifications: 7+ years in product analytics, strong SQL and Python skills required.
- Other info: Dynamic environment with a focus on mentorship and analytical excellence.
The predicted salary is between 43200 - 72000 ÂŁ per year.
About the team
At ZOE, we are on a mission to empower people with the most advanced science and technology to transform their health. Data is at the heart of how we build products that deliver measurable health outcomes. You'll be part of the Product Analytics team, working closely with Product Managers, Designers, Engineers, and Nutrition Scientists. The team combines analytics engineering, experimentation, and product data science, and you'll play a leadership roleâsetting standards, mentoring others, and raising the bar for how data is used in product decisions.
About the role & impact
As a Lead Product Data Scientist, you will set the data science direction for our product organisation, combining product analytics, experimentation, and applied statistical / ML modelling to shape strategy, roadmap decisions, and member experience. You'll help teams decide when descriptive analytics is enough and when predictive or causal models materially improve decisions. We believe most decisions are reversible, so you'll balance rigour with pragmatismâmoving fast with ~70% evidence.
What youâll be doing:
- Raise the Bar in Experimentation: Lead product experimentation by introducing advanced statistical testing methods and platform improvements that deliver clear, confident insights for quicker decisions.
- Drive Product Strategy through Metrics: Own and evolve core product metrics across activation, engagement, retention, and monetisation to identify risks and leverage points.
- Predict & Influence User Behaviour: Use causal and inferential thinking (e.g., uplift modelling, regression, survival analysis) to move beyond "what happened" to "why." You'll develop lightweight ML models and segmentations that identify the specific levers driving longâterm retention and growth.
- Elevate Analytical Excellence: Set the standard for analytical methods and best practices across the team. You will mentor analysts and lead by exampleâstaying handsâon with data foundations (dbt/instrumentation) and showing the team how to turn raw data into influential narratives.
- Champion a Product-First Mindset: Apply a "so what?" filter to every project, ensuring complexity is only added when it sharpens a decision, and iterating quickly when reality proves a hypothesis wrong.
We think you would be great if you:
- 7+ years of experience in product analytics, data science, or experimentation-heavy roles.
- Degree in a quantitative field (Statistics, Maths, CS, Engineering, Physics, Economics, or similar).
- Deep fluency in SQL and Python.
- Handsâon experience with statistical modelling and applied ML, such as regression, classification, survival analysis, or timeâtoâevent modelling.
- Experience building and validating LTV, churn or retention models, and translating predictions into concrete product or lifecycle interventions.
- Strong judgment around model complexity vs. business valueâyou know when a heuristic beats a black box.
- Comfort with messy, realâworld data and imperfect signals.
- Ability to lead by influence, mentor others, and raise analytical standards.
- Clear, structured communicator to both technical and non-technical audiences.
- Thrive in fast-moving, low-process environments; aligned with our #ActFast value and comfortable acting on ~70% evidence.
Our hiring process
We know that "hiring processes" can sometimes feel like a black box. At ZOE, we aim for a process that is efficient, insightful, and enjoyable. It's a twoâway street: we want to get to know the real you, and we want you to get a true feel for life at ZOE.
- The "Meet & Greet" with Talent (45 min): First up, a deepâdive chat with one of our Talent partners. Think of this as a "look under the hood"âwe'll explore your journey so far, what gets you excited about our mission, and make sure we're aligned on the essentials like compensation, logistics, and rightâtoâwork.
- The Hiring Manager "Strategy Session" (45 min): This isn't just a tickâbox exercise; it's an intentional session where we talk shop. We'll dive into your technical approach and behavioural experience to see how you'll thrive in our team, while giving you a frontârow seat to our engineering culture and vision.
- The Remote Loop (The Final Stretch): We've grouped our final interviews into a "loop" (usually over Google Meet) to give us a 360âdegree view of your brilliance. It consists of three distinct sessions: Skills based interview (60 min), Cross Functional Interview (60 min), Leadership & Values (60 min).
The "Becoming a ZOEntist" Moment
If we're a match, we'll reach out quickly to discuss an offer and start planning how we can welcome you to the team.
Ready to thrive? We want to hear from you
The experience, skills, and attributes we've outlined are what we believe will help someone truly thrive in this role. However, we understand that talent comes in many forms. If you are genuinely excited about ZOE's mission and this opportunity, please don't hesitate to apply âeven if you don't meet every single requirement listed. We fundamentally value potential and commitment above all else. We are dedicated to fostering growth and providing opportunities for you to learn and develop alongside us.
Lead Product Data Scientist in London employer: Zoe Immersive, Inc.
Contact Detail:
Zoe Immersive, Inc. Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Lead Product Data Scientist in London
â¨Tip Number 1
Network like a pro! Reach out to current employees at ZOE on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for the interview process. This insider info can give you a leg up!
â¨Tip Number 2
Prepare for those interviews by brushing up on your technical skills. Since you'll be dealing with SQL and Python, make sure you're comfortable discussing your past projects and how you've used these tools to drive product decisions.
â¨Tip Number 3
Show off your analytical mindset! Be ready to discuss how you've approached problem-solving in previous roles. Use examples that highlight your ability to balance data-driven insights with practical business needs.
â¨Tip Number 4
Donât forget to apply through our website! Itâs the best way to ensure your application gets seen. Plus, it shows youâre genuinely interested in joining the ZOE team and being part of our mission.
We think you need these skills to ace Lead Product Data Scientist in London
Some tips for your application đŤĄ
Show Your Passion: When writing your application, let your enthusiasm for ZOE's mission shine through. We want to see why you're excited about using data to transform health and how you can contribute to our goals.
Tailor Your Experience: Make sure to highlight your relevant experience in product analytics and data science. We love seeing how your background aligns with the role, so donât be shy about showcasing your skills in SQL, Python, and statistical modelling.
Be Clear and Concise: Keep your application structured and easy to read. Use bullet points where possible and avoid jargon unless itâs necessary. We appreciate clear communication, especially when it comes to technical concepts!
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way for us to receive your application and ensures youâre considered for the role. Plus, it gives you a chance to explore more about our culture and values!
How to prepare for a job interview at Zoe Immersive, Inc.
â¨Know Your Data Science Stuff
Make sure you brush up on your SQL and Python skills, as well as your knowledge of statistical modelling and machine learning. Be ready to discuss specific projects where you've applied these skills, especially in product analytics or experimentation.
â¨Show Your Leadership Skills
Since this role involves mentoring and setting standards, think of examples where you've led a team or influenced decisions. Prepare to share how you've raised analytical standards in previous roles and how you can do the same at ZOE.
â¨Be Ready for Real-World Scenarios
Expect questions that test your ability to handle messy data and imperfect signals. Think about times when you've had to make decisions with limited evidence and how you balanced rigor with pragmatism.
â¨Communicate Clearly
Practice explaining complex concepts in simple terms, as you'll need to communicate with both technical and non-technical audiences. Prepare to demonstrate how you can turn raw data into compelling narratives that drive product decisions.