Data Scientist

We are looking for a Data Scientist with experience in developing and improving Machine Learning models, along with strong knowledge and interest in Generative AI. You will participate in data and AI projects, working on both existing models and the development of new solutions that deliver real business value.ResponsibilitiesDesign, develop, and optimize Machine Learning models.Analyze and work with large volumes of data and complex datasets.Evaluate, validate, and monitor model performance in production environments.Contribute to the development of solutions based on Generative AI and LLMs.Work with RAG architectures, embeddings, and AI solutions focused on business use cases.Collaborate with Data Science, Data Engineering, and other technical teams.Apply best practices throughout the model development lifecycle.Communicate insights and results to both technical and business stakeholders.QualificationsExperience as a Data Scientist with a strong understanding of Machine Learning.Experience developing and validating supervised learning models.Knowledge and hands-on experience with Generative AI, LLMs, and RAG.Strong proficiency in Python.Experience with Spark and PySpark.Knowledge of version control and model management tools such as Git and MLflow.Experience working with large-scale and complex datasets.Familiarity with Feature Stores, Agile methodologies, and DevOps is a plus.Previous experience in the insurance industry is highly valued.

We are looking for a Data Scientist with experience in developing and improving Machine Learning models, along with strong knowledge and interest in Generative AI. You will participate in data and AI projects, working on both existing models and the development of new solutions that deliver real business value., Experience as a Data Scientist with a strong understanding of Machine Learning. Experience developing and validating supervised learning models. Knowledge and hands-on experience with Generative AI, LLMs, and RAG. Strong proficiency in Python. Experience with Spark and PySpark. Knowledge of version control and model management tools such as Git and MLflow. Experience working with large-scale and complex datasets. Familiarity with Feature Stores, Agile methodologies, and DevOps is a plus. Previous experience in the insurance industry is highly valued.