Engineering Manager (Data Science Team)

Навыки

• A/B-тесты
• Атрибуция
• XGBoost / LightGBM / CatBoost
• Коммуникация
• Лидерство
• Machine Learning
• MLOps

О компании и продукте

• We’re a mission-led, product-driven team. We move fast, stay focused and take ownership – from brief to build to impact. Debate is encouraged. Decisions are shared. We care about craft, ship with purpose, and always raise the bar.
• You’ll be working with people who take their work seriously, not themselves. It takes commitment, resilience, and the drive to keep going when things get tough. Because better health outcomes are worth it.
• We support impact with meaningful reward. Here’s what that looks like:
• Competitive salary and annual reviews

Задачи

• Lead & develop a team of 6+ ML and Backend engineers - hiring, mentoring, and setting technical direction
• Own pLTV strategy - architect and evolve our core predictive lifetime value models that inform millions in UA decisions
• Stand up MMM - build our Marketing Mix Modeling capability: adstock and saturation modelling, channel contribution, and budget allocation, calibrated against our incrementality experiments
• Power real-time campaign management - develop the algorithms that optimise our UA campaigns across channels in real time
• Build production ML systems - from real-time prediction services handling millions of daily predictions to MMM models
• Drive cross-functional impact - partner with Growth, Product, and Finance to translate business problems into ML solutions
• Shape technical architecture - guide MLOps infrastructure, monitoring, and rapid iteration cycles
• Stay as hands-on as you choose - modeling, architecture decisions, technical problem-solving
• your call how deep you go

Требования

• Technical Leadership
• 7+ years applied ML experience building and deploying models in production
• 4+ years managing technical teams (ML engineers, data scientists, or similar)
• Expert knowledge of ML fundamentals: supervised/unsupervised learning, time series
• strong grounding in causal inference
• Experience with modern ML frameworks (TensorFlow, scikit-learn, CatBoost)
• Growth & Product Experience
• Experience with growth analytics, attribution modeling, or marketing effectiveness
• Understanding of user acquisition funnels and retention optimization
• Comfortable translating business requirements into technical roadmaps
• Strong communication skills - can explain complex models to executive stakeholders
• Production ML Systems
• Experience deploying ML models at scale
• Knowledge of MLOps practices: model versioning, monitoring, automated retraining
• Understanding of data engineering fundamentals and cloud platforms
• With 7M paid subscribers and the highest-rated experience in the App Store’s health category, we’ve spent 10 years earning trust at scale
• Now, we’re building the next generation of digital health – AI-powered, privacy-first, clinically backed – to help our users know their body better
• Alongside it, you'll stand up a Marketing Mix Modeling (MMM) capability to measure cross-channel effectiveness and inform budget allocation, and develop the algorithms to drive real-time UA campaign management
• Hands-on experience building Marketing Mix Models end to end, Bayesian or regression based

Будет плюсом

• Background in consumer tech, mobile apps, or health tech
• Knowledge of privacy-preserving ML techniques and A/B testing methodology

Условия

• Flo is the world’s #1 health & fitness app worldwide on a mission to build a better future for female health
• Backed by a $200M investment led by General Atlantic, we became the first product of our kind to reach a $1B valuation in 2024 – and we’re not slowing down
• We’re hiring a Data Science Lead in London to build and lead our Predictive Growth Optimisation team – pioneering ML models that power our user acquisition strategy, predict lifetime value, and optimise our $25M+ annual marketing spend across channels
• This role owns the strategy, development, and continuous improvement of Flo’s pLTV system - a mission-critical model reused across UA, AdTech, personalisation, and financial forecasting
• That is the core of the role
• You'll lead a team building production systems that directly impact our growth trajectory, staying as hands-on as you choose

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