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 george.hutchinson-binks@oxfordknight.co.uk (+44) 07885 545220 linkedin.com/in/george-hutchinson-binks-a62a69252
#J-18808-Ljbffr
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 george.hutchinson-binks@oxfordknight.co.uk (+44) 07885 545220 linkedin.com/in/george-hutchinson-binks-a62a69252
#J-18808-Ljbffr
