Lead Data Scientist - Industrial Digital Platform
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Our Industrial Digital Platform team is looking for a Lead Data Scientist to drive the development of advanced machine learning solutions applied to industrial and biological processes.
We are building a cutting-edge platform focused on optimising real-world operations through data, combining IoT, advanced analytics, and scalable cloud technologies. This is a high-impact role at the intersection of data science, engineering, and industrial innovation.
This is a strategic and hands-on leadership role, idóneo for someone who can define technical vision while managing and mentoring a team, and staying close to the modelling work when needed.
Conditions
- Permanent contract
- Hybrid model: 1 day of remote work per week
- Working hours: 9:30 am to 6:30 pm (Fridays until 14:30h)
- Location: Gta. Mar Caribe 1, Hortaleza | 28043, Madrid | Spain
Mission of the role
Lead the data science function within the industrial digital platform, defining modelling strategy and delivering high-impact predictive solutions to optimise industrial and biological processes.
You will act as the technical reference for data science, ensuring robust methodologies, scalable solutions, and strong alignment with engineering and operational teams.
Key responsibilities
Technical Leadership:
- Define the data science roadmap, modelling standards, and architectural decisions
- Act as the reference for methodological rigour and best practices
People Management:
- Lead, mentor, and grow a team of data scientists and analysts
- Support career development and foster a strong technical culture
Predictive Modelling:
- Design, build, and deploy machine learning models in production environments
- Own the full lifecycle from problem framing to deployment
Process Optimisation:
- Collaborate with process and biological engineers to improve efficiency, yield, and reliability
- Translate domain knowledge into data-driven models
IoT & Time-Series Analysis:
- Work with high-frequency sensor data and develop real-time inference pipelines
- Build robust feature engineering and signal processing workflows
Cross-functional collaboration:
- Partner with Data Engineers, architects, and operations teams
- Ensure models are integrated, monitored, and used in decision-making
MLOps & Governance:
- Implement best practices in model versioning, monitoring, and reproducibility
- Ensure scalable and reliable ML operations
Profile
- 8+ years of experience in Data Science or Applied Machine Learning
- Proven experience deploying models in production
- Strong expertise in time-series modelling and IoT data
- Experience in industrial or biological environments (biogas, energy, chemical, etc.)
- Advanced Python skills (pandas, scikit-learn, PyTorch or TensorFlow)
- Experience leading data science teams
- Strong communication skills with non-technical stakeholders
- Degree in Data Science, Statistics, Engineering, or related field (PhD is a plus)
Core ML Skills
- Strong knowledge of supervised and unsupervised learning techniques
- Experience in time-series forecasting (ARIMA, LSTM, TFT)
- Feature engineering on sensor and IoT data
- Solid understanding of experimentation and model validation
- Experience with explainability tools (SHAP, LIME)
- Knowledge of optimisation xcskxlj methods (simulation, reinforcement learning, etc.)
Databricks & MLOps Stack
- Strong experience with Databricks (Delta Lake, MLflow, Workflows, Model Serving)
- Experience orchestrating ML pipelines end-to-end
- Model versioning, experiment tracking, and reproducibility
- Deployment of models for real-time and batch inference
- Monitoring model performance and data drift
- Familiarity with Azure Machine Learning and Azure ecosystem (ADLS Gen2, CI/CD)
Nice to Have
- Experience with digital twins
- Physics-informed modelling
- Real-time streaming (Event Hubs, Stream Analytics)
- Background in bioenergy or biological processes
- Knowledge of regulatory frameworks (ISO, GDPR)
Languages
- English — Fluent (required)
- Spanish — Highly valued
- Italian — Highly valued
What we offer
- Strategic role with real impact on industrial innovation
- Dynamic and fast-growing environment
- Opportunity to lead cutting-edge data science initiatives in the energy and industrial sector
If you’re interested, feel free to apply