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.
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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 xpzdshu 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)