Senior Data Scientist – AI Labs

Insud Pharma; Comunidad de Madrid; Vor Ort; EUR 70.000 - 110.000; Vollzeit

Benefits dieser Stelle

Ticket restaurant

Life & accident insurance

Training and language platform

Wellness platform with psychologist

Cabify for employees

Development plans

Internal mobility

Zusammenfassung

Insud Pharma is seeking a Senior Data Scientist for its AI Labs to own data science projects end-to-end across R&D, manufacturing, clinical ops, and supply chain. You will frame problems with business, select methodologies, develop and validate models, and push them into production with small squads.

Strong Python and cloud skills are essential, with fluency in Spanish and English. The role offers a dynamic startup-like environment within a large pharma group, with opportunities to work across

Qualifikationen

• 5+ years as a Data Scientist in industry with end-to-end project deployment.
• Experience with predictive ML, forecasting, causal inference, experimentation, optimization, clustering, graphs, and deep learning.
• Able to justify technical decisions and defend methodological choices.
• Autonomous contributor, driving day-to-day work with stakeholders.
• Strong Python skills and software engineering habits (Git, testing).
• Familiarity with cloud platforms (AWS/Azure/GCP) and LLMs is a plus.
• Professional Spanish and English.

Aufgaben

• Own a problem end to end: frame with business, choose methods, build and validate, deploy to production.
• Work in a small squad with PM and Engineer and key stakeholders; short feedback loops.
• Move between problems and business areas, managing multiple projects.
• Present technical trade-offs and findings to technical and non-technical stakeholders.

Kenntnisse

Python

Data Science

Forecasting

Causal inference

Experimentation

Optimization

Clustering

Graphs

Deep learning

Productivity & communication

Tools

Git

Docker

LLMs

Cloud (AWS/Azure/GCP)

Jobbeschreibung

Position: Senior Data Scientist – AI Labs

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 (Bionanopharma), with over 10,000 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're the Data Science team at AI Labs, the applied AI department of Insud Pharma, a global pharmaceutical group. Around 30 people (Data Scientists, AI Engineers, DevOps, Product Managers) building models and products across the whole pharma value chain: R&D, chemical synthesis, manufacturing, clinical operations, supply chain, pricing. Small teams, fast iteration, real ownership.

The challenge!

• Own a problem end to end: frame it with the business, choose the methodology, build the solution, validate it rigorously and take it to production.
• Work in a small squad, typically you, a Product Manager and an Engineer, plus the key stakeholders. Short feedback loops; your work is visible from day one.
• Move between problems and business areas. Projects vary in domain and technical approach, and you'll often have more than one in motion at a time. This is not a single-domain role.
• Turn results into decisions: present technical trade-offs and findings to both technical and non-technical stakeholders and defend every methodological choice.

What do you need?

• 5+ years as a Data Scientist in industry, having taken projects from problem framing to deployment.
• Breadth over domain depth: hands-on experience with several of these in real projects: predictive ML, forecasting, causal inference, experimentation, optimization, clustering, graphs, deep learning. We value people whose work generalizes across domains rather than one vertical (fraud, marketing, credit…).
• Rigorous by default: you can justify every technical decision and know when a simpler method beats a fancy one.
• Autonomous. You'll be the main contributor on your project, carrying the technical work and driving decisions day to day, with the Data Science team and its lead as a sounding board rather than a safety net.
• Strong communicator: you've presented to stakeholders and shaped decisions with your analysis.
• Genuine curiosity for the field: you read, you experiment, maybe you have side projects.
• Solid Python and software engineering habits (clean code, Git, testing). Cloud (AWS/Azure/GCP) and familiarity with LLMs are a plus.
• Professional Spanish and English.

Why here

• Startup mindset, corporate backing: autonomy, flat structure and fast decisions, with the data, scale and stability of a large pharma group behind you.
• Problems that matter: what you build ends up in factories, labs and clinical teams.
• A team that learns together: demo days, whiteboard sessions, honest feedback.
• Permanent contract, ticket restaurant, life & accident insurance, training and language platform, wellness platform with unlimited psychologist sessions, Cabify for employees, development plans and internal mobility.

Flexible start time from Monday to Friday

Training and language learning platform

Wellness platform with unlimited free psychologist sessions

Development plans, internal mobility policy.

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.