My client is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. A technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped the collaborative mindset, enabling them to solve the most complex challenges. They have a culture of innovation which continuously drives their ambition to deliver high quality returns for investors.
The role:
* Develop ETL pipelines to integrate and test very large alternative datasets for the Commodities desk in collaboration with quant researchers and data engineering teams.
* Architect, deploy and manage cloud-based systems for storing and exploring very large alternative datasets in collaboration with the AWS infrastructure team.
* Monitor, support, debug and extend existing Commodities trading and research infrastructure together with Researchers and Support Engineers.
Requirements:
* Comfortable in Python, in particular numerical libraries - numpy, pandas, matplotlib, etc.
* Basic knowledge of AWS.
* Basic knowledge of databases (e.g. SQL).
* Development practices - version control with Git, unit testing, etc.
* A quantitative mindset.
* Team player and collaborative attitude.
Nice to have:
* Experience creating dashboards or using data visualization software (e.g. Tableau, Dash).
* In-depth AWS experience (e.g. DynamoDB, RDS, S3, Lambda, AWS CDK).
* Advanced database knowledge (query optimisation, relational vs non-relational databases, etc.).
* Parallel computation.
* Experience with geographic data using geopandas, xarray.
* Financial knowledge is a plus but not required.
Contact
If this sounds like you, or you'd like more information, please get in touch:
George Hutchinson-Binks
(+44) 07885 545220
linkedin.com/in/george-hutchinson-binks-a62a69252
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