Location
London

Hours
Full Time

Salary
Negotiable

About the Role
Flo Health is the world’s #1 health & fitness app on a mission to build a better future for female health. With over 500 million downloads, 80 million monthly users, and 7 million paid subscribers, we are pioneering AI-powered, privacy-first, clinically backed digital health solutions. Backed by a $200M investment and recently reaching a $1B valuation, we continue to accelerate our growth and impact.

We are hiring an Engineering Manager to lead our Data Science team in London, focusing on Predictive Growth Optimisation. You will build and lead a team of ML and Backend engineers to develop and continuously improve Flo’s predictive lifetime value (pLTV) system, a mission-critical model that drives user acquisition strategy, marketing spend optimisation, and financial forecasting.

Your responsibilities will include architecting and evolving core ML models, establishing a Marketing Mix Modeling (MMM) capability to measure cross-channel effectiveness, and developing algorithms for real-time user acquisition campaign management. You will lead the design and deployment of production ML systems that handle millions of daily predictions and collaborate closely with Growth, Product, and Finance teams to translate business challenges into scalable ML solutions.

This role offers the flexibility to remain hands-on with modeling, architecture, and technical problem-solving as much as you choose, while shaping the technical direction and MLOps infrastructure of the team.

Experience
- 7+ years of applied machine learning experience building and deploying models in production
- 4+ years managing technical teams including ML engineers and data scientists
- Expert knowledge of ML fundamentals including supervised and unsupervised learning, time series analysis, and causal inference
- Proficiency with modern ML frameworks such as TensorFlow, scikit-learn, and CatBoost
- Experience with growth analytics, attribution modeling, and marketing effectiveness
- Strong understanding of user acquisition funnels and retention optimization
- Proven ability to translate business requirements into technical roadmaps
- Experience deploying ML models at scale and knowledge of MLOps practices including model versioning, monitoring, and automated retraining
- Understanding of data engineering fundamentals and cloud platforms

About you
- Strong technical leadership and mentoring skills
- Excellent communication skills with the ability to explain complex models to executive stakeholders
- Collaborative mindset to drive cross-functional impact with Growth, Product, and Finance teams
- Passionate about building scalable production ML systems that directly impact business growth

Qualifications
- Hands-on experience building Marketing Mix Models (Bayesian or regression-based) is a plus
- Background in consumer tech, mobile apps, or health tech is desirable
- Knowledge of privacy-preserving ML techniques and A/B testing methodology is advantageous