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Lead / Manager

Manager Data Scientist | Engagement & Platform

Confirmed live in the last 24 hours

Gympass

Gympass

Brazil (Remote)
Hybrid
Posted March 24, 2026

Job Description

 

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 schemas that feed the product, ensuring high-quality data for real-time decisioning and offline analysis.
  • Evaluation & Monitoring: Define and implement robust monitoring frameworks for the product, including short-term engagement metrics, longer-term retention, opt-outs, and intervention fatigue.
  • Leadership & People Management: Lead, mentor, and grow the data scientists of the team. Set technical direction, ensure high-quality delivery, and foster strong collaboration with Product and Engineering stakeholders.
  • Live the mission: inspire and empower others by genuinely caring for your own wellbeing and your colleagues. Bring wellbeing to the forefront of work, and create a supportive environment where everyone feels comfortable taking care of themselves, taking time off, and finding work-life wellness.

WHO YOU ARE

  • BSc., Master’s or PhD degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field;
  • At least 8 years of professional experience in Data Science, Machine Learning, or Applied AI roles;
  • At least 3 years of experience in people management, leading and developing data science teams;
  • Strong proficiency in Python and experience with ML frameworks (e.g., Vowpal Wabbit, PyTorch, or similar);
  • Strong foundation in experimentation, A/B testing, and large-scale experimentation design and analysis;
  • Experience working with Generative AI systems in production environments;
  • Solid problem-solving skills and ability to translate product goals into measurable, data-driven solutions;
  • Strong communication skills and ability to work cross-functionally with Product and Engineering teams
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