INNOCV Solutions
Data Scientist / ML Engineer (Madrid)
A Data Scientist/ML Engineer in Madrid who designs scalable data pipelines with PySpark, builds and optimizes machine learning models for predictive analytics, and deploys them on AWS SageMaker with Athena for querying, following MLOps best practices. Day-to-day work centers on Python, SQL, and Git-based collaboration within agile, cross-functional teams.
- Compensation
- Not disclosed
- Location
- Madrid, Spain
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Data science
- Posted
Skills
Must have
- 2–3 years of experience in Data Engineering, Machine Learning, or similar roles
- Advanced proficiency in Python, including 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 ML algorithms (regression, classification, clustering, hyperparameter optimization)
- Experience with AWS services, especially SageMaker and Athena
- Knowledge of MLOps practices and integrating/monitoring ML models in production
- Familiarity with Git and collaborative workflows using GitHub
- Strong analytical thinking and problem-solving skills
- Curiosity, autonomy, attention to detail, and a collaborative mindset
- Residence in Madrid
Full description
Who are we?
- We are digital natives and technology-neutral thanks to our rapid adaptation capabilities and problem-solving skills in any business situation.
- We are passionate about technology challenges that have a significant impact on business. 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.
Who are we?
We are part of the Alkemy Group, specializing in driving growth through our technological expertise, tackling complex challenges, and fostering operational excellence.
- We are digital natives and technology-neutral thanks to our rapid adaptation capabilities and problem-solving skills in any business situation.
- We are passionate about technology challenges that have a significant impact on business. 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 invite you to get to know us in depth by exploring the various sections of our website.
What will you do?
- 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.
What do we value?
- 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.