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.
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 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)