Position
Data Scientist
Location
Madrid (Chamberí area).
About the Company
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.
The activities 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.
About the Team
The Data Science team within AI Labs, the applied AI department at INSUD PHARMA, consists of 30 professionals (AI Engineers, Data Scientists, DevOps Engineers, Product Managers). The team works across the breadth of the company, building products, models, and analytical solutions.
AI Labs operates with a startup mindset: flat, collaborative, fast‑moving. The environment encourages regular demo days and whiteboard sessions, with a cross‑disciplinary dynamic.
Responsibilities
* Collaborate with small, cross‑functional teams led by a Product Manager, Engineer, and 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 technical and non‑technical audiences.
Qualifications
* Strong understanding of statistics, machine learning, and data mining techniques.
* Expertise in Python and data science libraries (NumPy, Pandas, scikit‑learn, TensorFlow, etc.).
* Strong knowledge of data preprocessing, feature engineering, and model evaluation.
* Proven ability to explain complex technical concepts to non‑technical audiences.
* Knowledge and experience in causal inference methodologies valued.
* Experience with deep learning architectures and natural language processing beneficial.
* Familiarity with Large Language Models (LLMs) and business applications.
* Experience with version control systems (Git) and collaborative development practices.
* Clean, maintainable code and familiarity with software engineering best practices.
* Experience with cloud platforms (AWS, Azure, Google Cloud) and their ML services.
* Experience with big data technologies (Spark, Hadoop) and SQL databases a plus.
* Proficiency in Spanish and English, written and verbal.
Benefits
* Versatile start time, Monday to Friday.
* Permanent contract.
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