We are digital natives and technology-neutral thanks to our rapid adaptation capabilities and problem-solving skills in any business situation.
To address these, we have high-performance teams and the ability to quickly and effectively combine technologies.
We support our clients in their digital evolution to achieve maximum efficiency in their businesses, leveraging our extensive multi-sector experience.
We are digital natives and technology-neutral thanks to our rapid adaptation capabilities and problem-solving skills in any business situation.
To address these, we have high-performance teams and the ability to quickly and effectively combine technologies.
We support our clients in their digital evolution to achieve maximum efficiency in their businesses, leveraging our extensive multi-sector experience.
Design, develop, and maintain scalable data pipelines using PySpark to efficiently process large volumes of data.
Develop, test, and optimize Machine Learning models for predictive analytics, including regression, classification, and clustering techniques.
Manage and deploy Machine Learning environments and workflows using AWS SageMaker, while leveraging Athena for data querying and analysis.
Integrate Machine Learning models into production pipelines, ensuring proper monitoring, maintenance, and continuous improvement through MLOps best practices.
Collaborate closely with cross-functional teams to understand business challenges and translate them into data-driven solutions.
Conduct advanced data analysis using Python and SQL to deliver actionable insights.
Work collaboratively with multidisciplinary teams using Git/GitHub and agile development methodologies.




2–3 years of experience in Data Engineering, Machine Learning, or similar roles.
~ Advanced proficiency in Python, including libraries such as Pandas, NumPy, and Scikit-learn.
~ Strong SQL skills for data querying, transformation, and analysis.
~ Hands-on experience with PySpark for large-scale data processing.
~ Solid understanding of Machine Learning algorithms, including regression, classification, clustering, and hyperparameter optimization techniques.
~ Experience working with AWS services, especially SageMaker and Athena.
~ Knowledge of MLOps practices and experience integrating and monitoring ML models in production environments.
~ Familiarity with Git and collaborative development workflows using GitHub.
~ In this company, you can be yourself and work with colleagues equally passionate about technology and innovation, ready to support you at all times. To that end, we invest in your professional development with training, tech breakfasts, and attendance at forums. We are advocates of continuous learning , which is why we provide a personal budget for staying up to date with market trends.
Due to the emphasis we place on flexibility and work-life balance , we won the Madrid Flexible Company Award in 2020 and received an honorable mention in 2022.
Professional Training & Certifications
Adaptable hours
Fridays and summer 7h.
Every three years, 6 extra days off.
Bring a friend and benefit from it
To learn more about us, the protagonists of INNOCV will share more about the company.
If you identify with our work philosophy and share our passion for INNOvation and Code Vocation , we want to meet you!

📌 Data Scientist / ML Engineer (Madrid)
🏢 INNOCV Solutions
📍 Madrid