Staff Data Scientist

Wellhub (formerly Gympass) is a corporate wellness platform that connects employees to fitness, mindfulness, therapy, nutrition, and sleep partners with a single subscription. Founded in 2012 and headquartered in NYC, Wellhub has a growing global team in 11 countries. At Wellhub you have the opportunity to build a career in a high-growth tech company that places wellbeing at the foundation of its culture.

We are hiring a Staff Data Scientist to our Fraud Prevention team in Brazil . This team identifies, prevents, and removes fraudulent actors from Wellhub. We work with all teams to identify fraud vectors and determine actions to prevent or remove them. We are looking for a talented Data Scientist to study and apply fraud models over different behaviors and entities.

• Build production systems that identify and remove fraudsters from Wellhub.
• Own the end-to-end lifecycle of machine learning models, from ideation and prototyping to production deployment and monitoring.
• Prototype, implement and productionize new anti fraud solutions at scale.
• Ensure successful deliveries and the long-term technical health of our journeys.
• Maintain a high bar for code quality and ensure the team is proud of their work.
• Apply technology best practices.
• Participate in incident resolution and troubleshooting in the production environment.
• Live the mission by caring for your wellbeing and your colleagues, fostering a supportive environment that promotes work-life balance.

• Bachelor's degree in Computer Science, Computer Engineering, or related discipline or equivalent practical experience.
• Experience as a data scientist delivering consistent results in a business setting.
• Knowledge of machine learning algorithms (supervised and unsupervised) and hands-on experience prototyping and implementing them.
• Proficiency in Python and SQL; a lifelong learner with a passion for emerging technologies.
• Strong communication skills, able to explain technical concepts to different audiences.
• Data-driven mindset, business impact focus, and experience with experimentation.
• Output-driven with experience working in high-uncertainty environments.
• Curious, collaborative, and strong teamwork.
• Proficient experience with fraud and anomaly detection models.
• Experience with public clouds, especially AWS (Nice to have).
• English proficiency.
• For this role, prior experience in data science, MLOps and Python are mandatory requirements.

We recognize that applicants come from diverse backgrounds. We encourage you to apply even if you do not meet 100% of the listed requirements. For this role, prior experience in data science, MLOps and Python are mandatory.

We are a wellness company committed to the health and wellbeing of our employees. Our flexible program allows you to tailor benefits to your needs.

• WELLNESS: Health, dental, and life insurance.
• FLEXIBLE WORK: Flexible hybrid or full remote model; home office stipend and monthly flexible work allowance.
• FLEXIBLE SCHEDULE: Ability to adjust working hours based on personal schedule and business needs.
• WELLHUB: Access onsite gyms and fitness programs; digital wellness resources; Gold plan at no cost and other premium plans at discounted prices.
• PAID TIME OFF: Vacations after 6 months plus 3 days per year, plus 1 day per year of tenure (up to 5 extra days) and a birthday off.
• PAID PARENTAL LEAVE: 100% paid parental leave and extended maternity leave.
• CAREER GROWTH: Opportunities for personal and professional growth with strong investment in employee development.
• CULTURE: A supportive, global, high-growth technology company with a trust-based, flexible, and integrity-driven culture.

Questions on how we treat your personal data? See our Aviso de Privacidade para Candidatos.

We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, gender identity or expression, sexual orientation, age, disability, national origin, veteran status, or any other basis protected by law.

For this role, we strongly encourage you to apply even if you do not meet 100% of the requirements.