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Manager Data Scientist | Engagement & Platform

Gympass
2 months ago
Full-time
Remote
Worldwide
Remote Data

 

Your wellbeing, our mission. Join a company shaping a healthier world.

GET TO KNOW US

At Wellhub we're revolutionizing workplace wellness. Our platform connects employees worldwide to the best partners for fitness, mindfulness, therapy, nutrition, and sleep—all in one simple subscription. Headquartered in NYC with team members in Europe, North America and South America, we’re on a mission to make every company a wellness company.

We believe work should be fulfilling, inspiring, and balanced. Here, you’ll find a team that values wellbeing, collaboration, and different perspectives, where passion and creativity push boundaries to create real impact. Your contributions will help shape a healthier, more balanced world for you and millions of people globally. 

Join us in redefining the future of wellbeing!

 

THE OPPORTUNITY

We are hiring a Manager Data Scientist to our Engagement & Platform team in Brazil! This is a Remote – Brazil position, meaning you can work from anywhere within the country. Please note that this role is only open to candidates in Brazil. 

As a Data Science Manager, you will be responsible for shaping the ML and experimentation strategy behind our engagement system, including ML models (e.g., contextual bandits, reinforcement learning, classification, etc) and AI agents that produce dynamic, personalized nudges to the Wellhub AI users. You will work closely with Product, Engineering, and Data Scientists to design, build, and evaluate systems that operate at scale. This role also includes people management, mentoring, and raising the bar on scientific rigor across the team.

YOUR IMPACT

  • Machine Learning Systems: Design and develop ML models for outreach personalization, including contextual bandits, reinforcement learning, and classification models.
  • AI Agents: Design and develop AI agents that generate dynamic, personalized nudge content and conversational interventions.
  • A/B Testing & Experimentation: Design and analyze large-scale A/B tests and experimentation frameworks to evaluate ML models, data-driven signals, nudges, and content strategies. Define success metrics and ensure statistically sound experimentation practices.
  • Data Pipelines & Analytics: Collaborate on the design of data pipelines and event sche