Commodities Quant/Data Scientist - Top Multi Strat Fund
Location: London, United Kingdom
Type: Full Time
Internal Number: 20227990
Senior Commodities Quant/Data Scientist - Top Multi Strat Fund
London or US based
Our client is seeking a Senior Commodities Pricing Data Specialist to work in their industry-leading Commodities Data team. This business unit is one of the newest and fastest growing profit centers at the firm, rapidly onboarding new markets and staff around the globe with ambitions to add physical trading capabilities. This role will be part of a highly collaborative and impactful team helping to grow their Commodities business.
As the Senior Commodities Pricing Data Specialist, you will be responsible for the following:
Specifying the rules for analyzing historical price data for commodities markets.
Leveraging your deep expertise in commodities markets and the instruments that trade on them to help build an industry-leading data product.
Partnering with the Risk team and Commodities Portfolio Management teams to help deliver quality-assured market data across numerous markets, such as power, gas, oil, metals, ags, etc.
Acting as the subject matter expert to help design solutions being built by the Commodities Data Team.
Applying your knowledge of commodities markets and instrument pricing to analyze and model commodities data.
Accelerating the data quality efforts of the Commodities Data Team by applying your passion for timely, complete, accurate data.
5+ years of experience working with pricing / market data in the Commodities space.
Deep understanding of Commodities markets, including most or all of the following: oil, power, gas, metals, agricultural products, freight.
Experience participating in the commodities trading process a strong plus.
Excellent communication skills.
A proven track record of working with data in the Commodities space and a passion for data quality.
A strong background in data analysis and analytics.
Good technical skills in data wrangling technologies, including Python (Pandas) and SQL.