[Hiring] Data Scientist / ML Engineer @INNOCV Solutions S.L.U.

Role Description

• 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.

Qualifications

• 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.
• Strong analytical thinking and problem-solving skills.
• Curiosity, autonomy, attention to detail, and a collaborative mindset.

Benefits

• 100% remote work
• Flexible hours
• Special timetable: Fridays and summer 7h.
• Individual budget for attending forums and training
• English classes
• Health insurance
• Every three years, 6 extra days off.
• Day off on your birthday
• Bring a friend and benefit from it
• Flexible compensation
• Wellness - Gympass
• Volunteering opportunities
• Company events and team buildings