Project description
Work alongside software engineers and data scientists to ensure that quantitative research models are effectively developed, tested, and deployed in production environments.
Responsibilities
- Creation and maintenance of CI/CD pipelines for efficient deployment of ML models
- Data management - e.g. connect with data sources and create ETL pipelines, cleanse the data, create datasets for model retraining
- Create pipelines for automated model testing
SKILLS
Must have
- 1. Strong knowledge of Python and familiarity with relevant libraries, e.g. scikit-learn, TensorFlow, and PyTorch.
2. Data - SQL, ETL, Pandas.
3. Containerization (Docker / Kubernetes) and Cloud (AWS).
Nice to have
• Experience in applying MLOps principles to financial domain.
• Familiarity with Databricks.