Factorial

Data Scientist – ML & AI

🇪🇸 Barcelona, ES Presencial TI Intermédio Publicado Mai 4, 2026

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LocalizaçãoBarcelona, ES

ModalidadePresencial

SenioridadeIntermédio

CategoriaTI

Categoria ITData Science e ML

IdiomaEnglish

Publicado4 de Maio de 2026

Última verificação8 de Maio de 2026

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 the role. Talk a lot: Participate in team rituals and stakeholder sessions to ensure what we build solves real business needs and can be adopted effectively. What we'd love to see in your background 2+ years of experience as a Data Scientist, Machine Learning Engineer, or similar role working on applied ML projects. Experience with classic machine learning models such as classification, regression, clustering, forecasting, ranking, or recommendation systems. Ability to own end-to-end ML projects, from business problem definition and data exploration to model development, deployment, monitoring, and iteration. Strong analytical skills and ability to translate ambiguous business questions into structured, measurable data science problems. Solid experience with Python and SQL, and familiarity with common ML/data science libraries. Experience working with production-oriented ML workflows, including model evaluation, testing, monitoring, documentation, and collaboration with Engineering teams. Good stakeholder management skills, with the ability to communicate clearly with both technical and non-technical audiences. Strong ownership mindset, autonomy, curiosity, and ability to navigate ambiguity. Comfortable working in English and with distributed teams. Willingness to work from our Barcelona office 4 days per week, with 1 day working from home. Strong plus: Experience deploying ML models into production environments. Experience with feature engineering, data pipelines, experimentation, or model monitoring. Experience working in SaaS, B2B products, HRTech, fintech, or business management software. Familiarity with MLOps practices and tools. Experience collaborating closely with Product and Engineering teams. How We Work 🏡 We follow an office-first, flexible approach because we believe the best products are built when people collaborate face-to-face. For this role, we’re looking for someone who can work from our Barcelona office 4 days per week, with 1 day working from home. This helps the team connect, brainstorm, align with stakeholders, and ship together, while keeping flexibility for deep work and personal balance. Perks of being part of our team 💆 We care about people and we also offer a lot of benefits for employees: High growth, multicultural and friendly environment 🤝🏽 Continuous training and learning based on your needs 🤓 Alan private health insurance 🩺 Healthy life with Wellhub (Gyms, pools, outdoor classes) 🧘🏽‍♀️ Save expenses with Cobee 💰 Language classes with Preply 👩🏽‍🏫 Get the most out of your salary with Payflow And when at the office... Breakfast in the office and organic fruit 🍏 Nora and other discounts 🍱 Pet Friendly 🐶 Join Factorial, where people grow 💗 Diversity is part of our culture, we have more than 43 nationalities in our teams and we are infused in an inclusive environment for all employees and candidates. Please feel free to apply with the way it suits you better! (blind resume, identity pronouns, cover letter, etc). We do not discriminate on any aspect, in fact; Factorial encourages everyone to join us! About us 🚀 Factorial is an innovative Business Management Software solution designed to streamline company processes for small and medium-sized enterprises. Founded in 2016, our mission is to help companies automate workflows, centralize people data, and make better business decisions. With customers across over 60 countries worldwide, we've built a diverse team that's driving change in the business management tech space. Join us as we continue our rapid growth journey! 🌎 Our Values 🫀 We own it: We take responsibility for every project. We make decisions, not excuses. We learn and teach: We're dedicated to learning something new every day and, above all, sharing it. We partner: Every decision is a team decision. We trust each other. We grow fast: We act fast. We believe that the worst mistake is not learning from them.