In a few words

Position: Data Scientist

Location: Madrid (Chamberí area).

Want to know more? 👇

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 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.

Ready to be a #Challenger?

What are we looking for? 🔎

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.

How the team works:

AI Labs operates with a startup mindset within Insud Pharma. The department is young, and the culture reflects that: flat, collaborative, and fast-moving. 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.

We hold regular demo days where teams present their work, as well as whiteboard sessions where we tackle problems together. The cross-disciplinary dynamic is genuinely strong. The office is located in central Madrid (Chamberí, near Eloy Gonzalo), well connected and situated in a vibrant part of the city.

The challenge!

• Collaborate with small, cross-functional teams. Each project is run by a small group — typically a Product Manager, a Data Scientist, an Engineer, and key stakeholders. Iteration is fast, feedback loops are short, and your contribution is visible from day one.
• 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.

What do you need?

• 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.
• Proven ability to translate complex technical concepts into clear, actionable insights for non-technical audiences.
• Knowledge and experience in causal inference methodologies will be highly valued.
• Knowledge of deep learning architectures and natural language processing is beneficial.
• Familiarity with Large Language Models (LLMs) and their applications in business contexts is a plus.
• Experience with version control systems (e.g., Git) and collaborative development practices.
• 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.

Our benefits!

⏰ Flexible start time from Monday to Friday

📜 Permanent contract.

🥼 Life and accident insurance.

🍽️ Ticket restaurant

💻 Training and language learning platform

💆🏻 ♀️ Wellness platform with unlimited free psychologist sessions

🚕 Cabify transportation service for employee use

📈 Development plans, internal mobility policy.

⭐ Many more!

What will the Selection process be like? 🕵️

➡️ Stay tuned to your phone and email! The first thing we will likely do is contact you through one of the two channels.

➡️ Prepare well! We will continue with an in-person/virtual interview depending on availability and what we agree upon; there may be one or two interviews in the process, and depending on the type of process, there may also be some kind of test.

➡️ Wait for the result! We care that you feel guided throughout each selection process and know what to expect from us, so we will always try to inform you of the status of the process.

🔷 Do you think this offer is not for you? 🔷

Follow us on social media like LinkedIn/Instagram and stay tuned for any offers we may release; the opportunity to be a new Insuder is waiting!

#InsudPharma #Challenger #Insuder #InsudTalent

COMMITMENT TO EQUAL OPPORTUNITIES

The InsudPharma group is aware that business management must align with the needs and demands of society, and therefore assumes the commitment to equal opportunities and treatment between men and women, as stated in the current regulations on the matter - Organic Law 3/2007, and we do not discriminate against any person on the grounds of ethnicity, religion, age, sex, nationality, marital status, affective or sexual orientation, gender identity or expression, disability, or any other personal or social circumstance.