What you'll do
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- Design, develop, and validate machine learning models through iterative experimentation and PoC cycles.
- Work directly with customers and stakeholders to understand business problems, define use cases, KPIs, and success criteria.
- Develop forecasting, predictive, and analytical models, with strong focus on time series use cases.
- Collaborate closely with Product Owners, Data Engineers, Data Analysts, and MLOps Engineers to deliver AI and ML solutions efficiently.
- Perform feature engineering, model validation, and model performance analysis.
- Build demo-ready PoCs and visualizations to communicate results and insights to stakeholders.
- Track experiments, metrics, and model evolution using MLflow.
- Work with analytical datasets and contribute to the definition of datasets and features for ML use cases.
- Contribute to technical standards, best practices, and AI/ML solution design.
What we're looking for
- 4+ years of experience as a Data Scientist, ML Engineer,



or similar role focused on analytical and ML solutions.
- Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field.
- Strong background in machine learning.
- Experience managing ML experimentation cycles, model lifecycle, and production model maintenance, using tools such as MLflow or similar.
- Proficiency in Python and experience working with SQL.
- Experience working with analytical databases and large datasets.
- Familiarity with orchestration tools such as Apache Airflow and notebook-based experimentation workflows.
- Strong English communication skills, both written and spoken.
- Analytical mindset, fast learner, collaborative attitude, and customer-oriented approach.
- Experience working in Agile environments.
Our offer
- Permanent role.
- Hybrid working model (3 days of remote work/week).
- Flexible working hours.
- 30 business days of annual leave. xqbhyrx
- Adaptable remuneration plan.
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📌 Data Scientist (Madrid)
🏢 Tamarind Intelligence
📍 Madrid