Big data data scientist machine learning

With more than 1,000 clients across the globe, we have been rolling out solutions in major projects for over a decade – this is made possible by an international team of 7,600 people spread across 5 continents and more than 60 countries. Our solutions focus on four different Business Lines: Information System & Digital, Telecom, Life Sciences and Engineering. Amaris Consulting is your steppingstone to cross rivers of change, meet challenges and achieve all your projects with success.
Translate business challenges into data science use cases and deliver actionable pricing recommendations.

• Work with large datasets using Python and Spark, ensuring scalability and performance.
• Design, schedule, and monitor data and model pipelines using tools such as Airflow, ensuring reliability and traceability.
• Contribute to the implementation of CI/CD pipelines, ideally with Jenkins, to automate testing, deployment, and monitoring of models.
• Deploy and operate solutions in the cloud, preferably AWS (experience with Azure or GCP is also valued).
• Collaborate with business stakeholders, data engineers, and other data scientists in a multidisciplinary and international environment.
• Share best practices and contribute to the development of our Data & AI community within Amaris Consulting.

Experience as a Data Scientist, Machine Learning Engineer, or similar role (at least 4 years), ideally with exposure to pricing or optimization topics.

• Solid programming skills in Python (e.g. pandas, NumPy, scikit-learn, etc.).
• Hands-on experience with Spark (PySpark or similar) for big data processing.
• Experience with workflow orchestration tools, ideally Airflow, to manage data and model pipelines.
• Familiarity with CI/CD pipelines, preferably using Jenkins.
• Experience with cloud environments, ideally AWS (knowledge of Azure or GCP is also acceptable).
• Spanish fluent. English good.

Experience in retail, e-commerce, telecom, manufacturing, or industrial pricing environments.

• Knowledge of MLOps practices (monitoring, retraining, governance).
• Experience with Docker, Kubernetes, or similar technologies.
• Familiarity with data visualization tools (Power BI, Tableau, etc.).

Remote policy: Possibility to work onsite 2 or 3 days per week. A robust training system with our internal Academy and 250+ available modules.
• Through our WeCare Together program, you'll be empowered to design and lead projects that create real social or environmental impact, with the company's full support
For this purpose, we welcome applications from all qualified candidates regardless of gender, sexual orientation, race, ethnicity, beliefs, age, marital status, disability, or other characteristics .