About the role
Hi! 👋 DataOps / ML & AI: What’s the mission? Factorial is building a world-class data and AI platform to help teams make smarter decisions, automate complex workflows, and deliver more value to our customers. As a Mid Data Scientist, you’ll own end-to-end machine learning initiatives that directly impact our product, operations, and customer experience. You’ll work on classic ML models and data products that need to be accurate, reliable, explainable, and production-ready. You’ll collaborate closely with Product, Engineering, Data, Operations, Sales, and Customer Experience teams to translate business opportunities into robust ML solutions—balancing speed, impact, correctness, and long-term maintainability.
The role 📜 You’ll be part of the Data Ops – ML & AI team, working within a fast-growing Engineering and Data organization that builds high-impact systems across Factorial. You will identify, design, build, and deploy machine learning solutions across the full lifecycle: from problem framing and data exploration to model development, productionization, monitoring, and continuous improvement. You’ll work with classic ML models such as classification, regression, clustering, ranking, forecasting, or recommendation systems, depending on the business problem. You’ll be expected to understand when ML is the right tool—and when a simpler data-driven solution is better. You’ll partner with stakeholders across the company to understand their needs, define success metrics, communicate trade-offs clearly, and ensure the solutions we build are useful, adopted, and measurable. You’ll take ownership of projects from inception to production, working autonomously while collaborating with Data Engineers, Software Engineers, Product Managers, and business teams. Our stack & the day-to-day 🧑💻 We predominantly use Python, SQL, and modern data tooling to build, train, evaluate, and deploy ML solutions. You may work with libraries and frameworks such as pandas, scikit-learn, XGBoost, LightGBM, PyTorch, or equivalent tools depending on the use case. You’ll explore and model data from multiple sources, transforming business questions into clear datasets, features, experiments, and measurable outcomes. You’ll develop classic ML models and data products, ensuring they are well-tested, interpretable, monitored, and aligned with business needs. You’ll collaborate with Engineering and Data teams to bring models into production, defining clear interfaces, reliable pipelines, monitoring, and feedback loops. You’ll implement model evaluation and monitoring practices to detect performance degradation, data quality issues, and changes in user or business behavior. You’ll write documentation, share findings, join technical conversations, and communicate insights clearly to both technical and non-technical stakeholders. You’ll iterate in short development cycles, testing assumptions quickly, learning from results, and improving solutions based on real-world impact. Your first steps at Factorial Read a lot: Get to know Factorial’s product, customers, data ecosystem, and current ML & AI initiatives. Learn a lot: Pair with team members from Data, Product, Engineering, and business teams to understand the main opportunities and challenges where ML can create value. Analyze a lot: Explore datasets, identify patterns, validate assumptions, and help define clear success metrics for your first projects. Build a lot: Contribute to quick wins in ML workflows, model evaluation, data quality, automation, or stakeholder-facing insights. Fail a lot: We encourage experimentation. We understand that trying out new ideas, failing, learning, and improving is part of
