Data Scientist / Ml Engineer (Madrid)

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.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.If you are someone who enjoys staying up to date with the latest trends, is naturally curious, and likes exploring new ways of doing things, this is the place for you.If you consider yourself a true team player who believes in fair play above all else, there’s a team waiting for you!What do we offer you?In this company, you can be yourself and work with colleagues equally passionate about technology and innovation, ready to support you at all times.We want to see you evolve and grow with us.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.We care about well-being and happiness at work , which is why we listen to needs to offer the best working conditions in a unique human environment.Due to the emphasis we place on flexibility and work-life balance , we won the Madrid Flexible Company Award in ** and received an honorable mention in **.This is a WIN-WIN , and we have 42 benefits to offer you, but here are some highlights : Professional Training & Certifications ? Flexible hours Special timetable: Fridays and summer 7h.? Every three years, 6 extra days off.Day off on your birthday ? Bring a friend and benefit from it

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. If you are someone who enjoys staying up to date with the latest trends, is naturally curious, and likes exploring new ways of doing things, this is the place for you. If you consider yourself a true team player who believes in fair play above all else, there’s a team waiting for you!

In this company, you can be yourself and work with colleagues equally passionate about technology and innovation, ready to support you at all times. We want to see you evolve and grow with us. 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. We care about well-being and happiness at work , which is why we listen to needs to offer the best working conditions in a unique human environment. Due to the emphasis we place on flexibility and work-life balance , we won the Madrid Flexible Company Award in ** and received an honorable mention in **. This is a WIN-WIN , and we have 42 benefits to offer you, but here are some highlights : Professional Training & Certifications ? Flexible hours Special timetable: Fridays and summer 7h. ? Every three years, 6 extra days off. Day off on your birthday ? Bring a friend and benefit from it

We are part of the Alkemy Group, specializing in driving growth through our technological expertise, tackling complex challenges, and fostering operational excellence.