Position: Data ScientistINSUD PHARMA operates across the entire pharmaceutical value chain, providing specialized knowledge and experience in scientific research, development, manufacturing, sales, and marketing of a wide range of active pharmaceutical ingredients (API), finished dosage forms (FDF), and branded pharmaceutical products, adding value to human and animal health.
The activities of INSUD PHARMA are organized into three synergistic business areas: Industrial (Chemo), Branded (Exeltis), and Biotech (mAbxience), with over 9,000 professionals in more than 50 countries, 20 state-of-the-art facilities, 15 specialized R&D centers, 12 commercial offices, and more than 35 pharmaceutical subsidiaries, serving 1,150 customers in 96 countries worldwide. INSUD PHARMA believes in innovation and sustainable development.
We are the Data Science team within AI Labs, the applied AI department at Insud Pharma. We are a team of 30 professionals (AI Engineers, Data Scientists, DevOps Engineers, and Product Managers) working across the full breadth of the company, building products, models, and analytical solutions that directly inform and shape decision-making.
We are looking for an Applied Data Scientist with strong technical foundations who is eager to work across diverse and complex problem domains (R&D, drug manufacturing process optimization, clinical trials, and beyond). You will model problems from the ground up—defining the right framing, selecting appropriate methodologies, and owning solutions through rigorous development to full deployment.
We are seeking someone curious enough to tackle varied challenges (graph theory, embeddings, neural network forecasting models, causality, Bayesian optimization), rigorous enough to justify every technical and methodological decision, and independent enough to deliver end-to-end impact while taking full ownership of their work.
Beyond the Data Science team, you will work alongside AI Engineers, DevOps Engineers, and Product Managers who are equally committed to delivering high-quality work.The office is located in central Madrid (Chamberí, near Eloy Gonzalo), well connected and situated in a vibrant part of the city.
Each project is run by a small group — typically a Product Manager, a Data Scientist, an Engineer, and key stakeholders. Conduct exploratory data analysis to uncover patterns and insights in large datasets.Design, implement, and validate machine learning models and statistical methodologies to solve high-impact, real-world business problems.Translate technical findings into clear narratives, visualizations, and decision frameworks for both technical and non-technical stakeholders, enabling informed and data-driven decisions.
Strong understanding of statistics, machine learning, and data mining techniques.Expertise in Python programming, including proficiency with data science libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow...).Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.Experience with version control systems (e.g., Clean, maintainable code and familiarity with software engineering best practices.Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine learning services.Experience with big data technologies (e.g., Spark, Hadoop) and SQL databases is a plus.Proficient in Spanish and English in written and verbal communication.
Flexible start time from Monday to FridayPermanent contract.