Lead Data Scientist

Antal International; Madrid; Híbrido; EUR 70.000 - 90.000; Jornada completa

Descripción de la vacante

A prominent AI startup in Madrid is seeking a hands-on Lead Data Scientist to shape and drive AI/ML strategy across multiple product lines. In this high-impact role, you will lead a small, talented team, ensuring cutting-edge, production-ready, and scalable solutions. Responsibilities include designing ML models, collaborating with engineers, and mentoring team members. The ideal candidate has over 5 years of experience, strong classical ML expertise, and practical generative AI skills. This position offers a hybrid work model and competitive compensation.

Servicios

Hybrid Work Model

Learning & Development opportunities

Collaborative Team Culture

Early-Stage Impact & Career Growth

Competitive Compensation

Formación

• 5+ years as a Data Scientist or ML Engineer with hands-on coding and model development.
• At least 1 year mentoring or leading a small team.
• Fluent English for effective communication.

Responsabilidades

• Lead a small, multidisciplinary AI / ML team.
• Design, implement, and optimize ML models for various tasks.
• Collaborate with engineers to ensure accurate model integration.

Conocimientos

Classical ML Expertise

Generative AI frameworks

Python programming

Cross-functional collaboration

Herramientas

scikit-learn

XGBoost

LightGBM

AWS

Descripción del empleo

About the Role

We are looking for a hands‑on Lead Data Scientist to shape and drive AI / ML strategy across multiple product lines. This is a high‑impact role combining deep expertise in classical machine learning with practical experience in generative AI, ensuring solutions are cutting‑edge, production‑ready, and scalable.

You will lead a small, talented team, guiding end‑to‑end ML development while fostering technical excellence and innovation.

Key Responsibilities

• Lead a small, multidisciplinary AI / ML team.
• Align AI / ML initiatives with product goals while mentoring and developing team members.
• Design, implement, and optimize ML models for tasks including classification, regression, clustering, and forecasting.
• Build pipelines for training, evaluation, and testing to ensure model robustness, accuracy, and reproducibility.
• Collaborate with engineers to operationalize models for production.
• Ensure efficient inference and seamless integration into live systems.
• Explore and implement solutions using LLMs, vector databases, retrieval‑augmented generation (RAG), and agent frameworks (e.g., LangChain, LangGraph).
• Translate cutting‑edge AI research into practical, impactful applications.
• Work closely with AI Engineers, Data Scientists, and product teams to deliver scalable, production‑ready AI / ML features.
• Stay up‑to‑date on both classical ML and generative AI trends to maintain a competitive edge.
• Provide guidance, code reviews, and knowledge sharing to support the growth of junior team members.

Requirements

• Experience: 5+ years as a Data Scientist or ML Engineer with hands‑on coding and model development.
• Leadership: At least 1 year mentoring or leading a small team.
• Classical ML Expertise: Strong experience with scikit‑learn, XGBoost, LightGBM, and other regression/classification/clustering algorithms.
• ML Lifecycle Knowledge: Training, testing, inference, continuous evaluation.
Generative AI: Practical experience with LLMs and GenAI frameworks (e.g., LangChain, HuggingFace, CrewAI).
• Programming: Proficient in Python with clean, maintainable, efficient coding practices.
• Experimentation & Statistics: Solid foundation in experimental design and statistical methods for robust, reproducible models.
• Cloud & MLOps: Familiarity with AWS (preferred) and MLOps practices.
• Communication: Excellent problem‑solving and cross‑functional collaboration skills.
• Language: Fluent English for effective communication in a distributed global team.

Why Join

• Hybrid Work Model: Enjoy a flexible combination of office and remote work in Madrid.
• Learning & Development: Grow in an open, creative environment with opportunities to learn from experts.
• Collaborative Team Culture: Join a strong, multidisciplinary team where ownership and decision‑making are shared.
• Early‑Stage Impact & Career Growth: Contribute to a fast‑growing AI startup with international reach.
• Competitive Compensation: Attractive economic package aligned with experience.

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