.At Wellhub (formerly Gympass) (Permanent), in PortugalSalary: €48.000 - €57.000Expires at: 2025-06-09Remote policy: Full remoteApply now for a career that puts wellbeing first!GET TO KNOW USWellhub (formerly Gympass*) is a corporate wellness platform that connects employees to the best partners for fitness, mindfulness, therapy, nutrition, and sleep, all included in one subscription designed to cost less than each individual partner.
Founded in 2012 and headquartered in NYC, we have 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, and contribute to making every company a wellness company.
*Big news: Gympass is now Wellhub!
We are thrilled to announce our rebranding as Wellhub, marking a significant milestone in our journey.
This transformation reflects our evolution from a "pass for gyms" to a comprehensive employee wellbeing solution.
With our refreshed identity, we are poised to embark on an exciting new chapter of growth and expansion.
We are elevating our offerings, including a completely new app experience and an expanded network of wellbeing partners.
THE OPPORTUNITYWe are hiring a Data Scientist to our Gen AI team in Portugal!
As a Data Scientist specializing in Generative AI, you will play a crucial role in evaluating, measuring, and assessing Agentic systems that have as main goal improving the wellbeing of all Wellhub users.
You will collaborate with a multidisciplinary team of product managers, engineers and domain experts to create innovative AI applications that solve real-world problems.
YOUR IMPACTMetric Design & Analysis: Collaborate with product managers and engineering teams to define and measure metrics for user engagement, satisfaction, and chatbot effectiveness; Data Preparation: Perform data cleansing, transformation, and quality analysis on product data; Evaluation and Testing: Assist and design robust evaluation metrics to assess agentic AI performance, combining automated evaluation (LLM-as-judge), adversarial testing, human-in-the-loop evaluations, and custom behavioral metrics; Prompt Engineering: Craft reusable templates and clear instructions to measure system behavior, optimizing for challenging edge cases; LLM Observability: Design monitoring systems that track LLM behavior in production, capturing key metrics around information retrieval, hallucinations, and latency; A/B testing: Design, run, and analyze A/B tests to optimize chatbot interactions and user engagement; Dashboard Development: Create and maintain interactive dashboards using BI tools (e.G., Tableau, Power BI, Looker, Metabase) for real-time visualization of performance metrics and insights