INSUD 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. ¿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. 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.
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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.
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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. Versátil start time from Monday to Friday Permanent contract. Act as a point of contact between the Group Data Strategy team and the local Spanish team, helping ensure clear communication and alignment. ~ Support the local contribution to Group data initiatives, providing feedback on data availability, local needs, and business context. ~ Help ensure that Group data standards and methodologies are correctly applied in local projects. ~ Apply basic statistical, analytical, and machine‑learning techniques to contribute to models, indicators, and insights for new data products. ~ Perform exploratory data analysis (EDA) to assess data quality and understand trends or patterns. ~ Produce clear documentation, visualizations, and presentations to communicate the logic, methodology, and value of proposed data product features. ~ Contribute to the continuous improvement of our data science methodologies and product innovation pipeline. ~Bachelor degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field. ~ Proven track record in Data projects, with hands‑on involvement in analytics, modeling, and data‑driven solutions. ~ Proficient in SQL, Python, and Power BI for data manipulation, analysis, and visualization. ~ Strong knowledge of Microsoft ecosystem, with experience in Azure and Databricks environments highly preferred. ~ Familiarity with data governance principles and scalable data architectures. ~ Fuent in English and Spanish. Highly reliable, organized, and detail‑oriented, capable of managing tasks with a project management mindset. Advanced performance metrics To do so, we need a data scientist who can transform complex data into clear, actionable,