Data Science Manager

Description

**SKEELO: EMBARK ON THE JOURNEY THAT PLACES READING AT THE HEART OF EVERYTHING. ️** **WHO WE ARE** Skeelo is a digital reading platform that connects people to e-books, audiobooks, and minibooks through an accessible and personalized experience. Since 2019, we have leveraged technology to democratize access to reading and amplify its impact on personal development. We believe reading goes beyond leisure: it is a powerful tool to broaden knowledge, strengthen critical thinking, and drive human development. **OUR VIBE** We are distributed across Brazil and the world, driven by innovation, agility, and continuous learning—valuing diversity and transforming reading to adapt to people’s lives. We do all this with transparency in relationships, courage to innovate, focus on high performance, constant attention to delighting customers and readers, and agile deliveries that make a difference. Our work model is remote-first, maximizing the benefits of working from home: autonomous self-responsibility. However, we also value in-person connection and exchange; therefore, we hold several in-person gatherings in São Paulo \- SP to connect with fellow Skeelers. But relax—we always organize everything for you. **THE DATA TEAM NEEDS SOMEONE, AND WE WANT YOU WITH US!** **YOUR MISSION?** Build and lead Skeelo’s Machine Learning and AI function, structuring the models, agents, and processes that will transform the experience of millions of readers. You will implement dynamic personalization, bring our proprietary 7-year dataset into the product, and turn data and AI into a key competitive advantage. **YOUR DAY-TO-DAY AT SKEELO WILL LOOK LIKE THIS:** * Structure the Machine Learning and AI area within the Data team, defining stack, architecture, model governance, and MLOps best practices—from the first model to large-scale operations * Develop and deploy predictive models on our proprietary datasets, focusing on content recommendation, propensity modeling, and reader journey personalization (churn, reactivation, next best book, ideal format) * Introduce GenAI and AI agents into daily operations and product workflows: curation assistants, automation of internal processes, and conversational experiences that boost engagement and productivity * Recruit, train, and develop the team of data scientists, taking ownership in building the team that will grow alongside you * Collaborate closely with Data Engineering, Analytics, Product, Growth, and Software Engineering teams to integrate models into products, CRM systems, and business decisions—closing the full cycle from training to monitoring, retraining, and impact measurement against metrics such as D28, MAU, and minutes consumed **TO SUCCEED IN THIS ROLE, YOU’LL NEED:** * Proven experience building Machine Learning or Data Science functions from scratch—or during early maturity stages * Strong hands-on technical expertise in ML, with proficiency in Python and the modern data ecosystem (e.g., Databricks, AWS, SQL) * Real-world use cases of ML in production and at scale, delivering measurable business impact—not just proof-of-concept projects * Mastery of the full model lifecycle: training, deployment, performance and drift monitoring, retraining, versioning, and documentation (practical MLOps) * An experimentation mindset: A/B testing culture, causal measurement, and evidence-based decision-making * Advanced or fluent English **AND IT WOULD BE GREAT IF YOU ALSO HAVE:** * Experience with digital content platforms, user consumption, or behavioral analytics—where personalization and recommendation are core to the product * Hands-on experience applying GenAI and AI agents to real-world scenarios (RAG, assistants, LLM-powered process automation) * Experience integrating models into apps and CRMs alongside software engineering teams * A teaching-oriented profile and strong communication skills—able to translate complex ML concepts for business stakeholders and navigate fluidly across departments