At a Glance
- Tasks: Lead the pLTV platform development and collaborate with data scientists to drive growth.
- Company: Join Flo, the world's top health app focused on female health innovation.
- Benefits: Competitive salary, performance incentives, generous leave policies, and professional growth opportunities.
- Other info: Hybrid work model with a supportive and inclusive company culture.
- Why this job: Make a real impact in digital health while working with cutting-edge AI technology.
- Qualifications: Experience in machine-learning products and strong analytical skills required.
The predicted salary is between 75600 - 92400 Β£ per year.
A decade of building β and we're still accelerating.
Flo is the world's #1 health & fitness app worldwide on a mission to build a better future for female health.
Now, we're building the next generation of digital health β AI-powered, privacy-first, clinically backed β to help our users know their body better.
As Senior Product Manager for Predictive Growth at Flo, you'll own Flo's predicted Lifetime Value (p LTV) platform across i OS, Android, and Web. p LTV is the shared signal behind UA bidding, budget allocation, creative-testing prioritisation, finance forecasting, and roadmap decisions across the organisation β making it one of the highest-leverage PM roles in growth.
You'll work with a team of data scientists, machine learning engineers, and data engineers running Flo's production p LTV models across short-horizon (intra-day) and long-horizon (M15+) predictions.
You'll also help scale Flo's in-house agentic experimentation system β already delivering 30%+ quality gains β and contribute to the next generation of Flo's marketing measurement stack, including Marketing Mix Modeling and incrementality testing.
Proven experience owning machine-learning or data-driven products in production β predictive scoring, propensity, ranking, forecasting, or similar data-rich products.
Strong fit for current Product Managers; Hands-on delivery instincts β equally comfortable in Jira (writing specs, defining epics, refining the sprint backlog, unblocking the team) as in strategic planning and stakeholder management.
Hands-on partnership with data science and machine-learning engineering teams β partnering on model evaluation, retraining cadence, feature decisions, and release discipline.
Strong analytical fluency β SQL proficiency, comfort interpreting model evaluation metrics, and the habit of interrogating performance at segment, cohort, and campaign level rather than blended aggregates.
Demonstrated ability to influence senior cross-functional stakeholders across marketing, finance, analytics, and engineering β translating technical model behaviour into commercial decisions.
Comfortable in fast-paced, ambiguous environments β balancing platform investments against fast-cycle experimentation, with shifting priorities and competing demands.
Working knowledge of mobile and web user acquisition β how bidding, attribution, and campaign optimisation actually work, including privacy frameworks such as SKAN/ATT or Privacy Sandbox.
Exposure to Marketing Mix Modeling, incrementality testing, holdout design, or causal inference techniques.
Owning Flo's p LTV product roadmap end-to-end across i OS, Android, and Web β driving accuracy improvements, expanding feature coverage, extending prediction horizons, and pushing p LTV into new decision domains (creative testing, product roadmap, pricing, hypothesis validation) alongside its existing UA and Finance use cases.
Partnering with data scientists and engineers on feature strategy β deciding which inputs the model consumes and ensuring those features are available reliably in production.
Operating rigorous release discipline β gated rollouts, shadow-mode evaluation, drift detection, automated retraining, and post-launch calibration β so production models stay accurate as data distributions and platform policies evolve.
Working closely with data scientists and analysts to investigate model quality issues β country-level miscalibration, cohort drift, signal anomalies β and feeding findings back into the next iteration.
Helping scale Flo's agentic ML experimentation system from hundreds toward thousands of model runs β compounding quality gains back into production.
Reporting model performance and strategic recommendations into monthly leadership reviews and quarterly investment decisions.
LI-Hybrid #LI-AJ1
We care about craft, ship with purpose, and always raise the bar.
Competitive salary and annual reviews
~ Opportunity to participate in Flo's performance incentive scheme
~ Paid holiday, sick leave, and female health leave
~ Enhanced parental leave and pay for maternity, paternity, same-sex and adoptive parents
~ Accelerated professional growth through world-changing work and learning support
~ In-person collaboration and work in a hybrid model, with 3 days per week spent in the office
~5-week fully paid sabbatical at 5-year Floversary
~ Flo Premium for friends & family, plus more health, pension and wellbeing perks
Diversity, equity and inclusion
We're proud to be an equal opportunity employer, and we welcome applicants from all backgrounds, communities and identities.
Senior Manager Product Planning in London employer: Flo Health
Flo Health is an exceptional employer, offering a dynamic work culture in the heart of London where innovation thrives. As a Data Science Lead, you'll not only have the opportunity to shape cutting-edge ML models but also benefit from a collaborative environment that prioritises employee growth and development. With competitive compensation and a focus on work-life balance, Flo Health stands out as a place where your contributions directly impact user acquisition and marketing strategies.
StudySmarter Expert Adviceπ€«
We think this is how you could land Senior Manager Product Planning in London
β¨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Flo Health!
β¨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Manager Product Planning at Flo Health.
β¨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Flo Health.
β¨Apply Directly through Our Website
When you find a suitable opening like Senior Manager Product Planning at Flo Health, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesnβt love a direct application? Itβs easier than navigating through job boards!
We think you need these skills to ace Senior Manager Product Planning in London
Some tips for your application π«‘
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Donβt forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Flo Health, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why youβre a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Flo Health. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Flo Health
β¨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
β¨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, itβll really make us stand out!
β¨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Flo Health!
β¨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how weβd approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.