We are looking for a Data Scientist to join a strategic AI and GenAI project within the financial services sector, working closely with MLOps and Data Engineering teams.
Es posible que un gran número de candidatos se presenten a este puesto, así que asegúrese de enviar su CV y su solicitud lo antes posible.
The role focuses on developing advanced models and ensuring they are scalable, production-ready, and aligned with modern data and ML architectures.
Role Description
As a Data Scientist, you will work with large volumes of data to develop predictive models and machine learning solutions.
You will be part of a modern ecosystem where models are deployed into production through robust pipelines, collaborating closely with MLOps and Data Engineers.
Responsibilities
* Develop, train, and validate machine learning models for business use cases
* Perform exploratory data analysis (EDA) and feature engineering on complex datasets
* Collaborate with Data Engineers on data preparation and transformation at scale
* Work with MLOps teams to industrialize, deploy, and monitor models
* Contribute to the continuous improvement of ML pipelines (testing, versioning, reproducibility)
* Communicate insights and recommendations to technical and business stakeholders
Tech Stack / Skills
* Strong experience xohynlm with Python (pandas, numpy, scikit-learn or similar frameworks)
* Solid knowledge of SQL and working with large datasets
* Experience developing machine learning models (supervised and unsupervised)
* Familiarity with cloud environments (AWS, GCP, or Azure)
* Experience working in production environments with ML pipelines
* Knowledge of MLOps tools (MLflow, Airflow, Kubeflow, or similar)