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Commodities Fundamental Analyst(m/w/x)
Building supply/demand models for agricultural commodities, analyzing market developments for trade ideas. Advanced degree in Math/Stats/Quant Finance and Python coding skill required. Exposure to systematic trading strategies, direct impact on market decisions.
Requirements
- Advanced degrees (MSc preferred) in Mathematics/Statistics or Quantitative Finance
- Experience in quantitative research (ideally through prior internship or related position, especially in commodities trading)
- Experience in highly quantitative trading asset classes (power) and systematic trading (plus)
- Python coding skill (required)
- Ease with Excel/VBA (plus)
- Passion for investing and commodities market trends
- Excellent writing skills
- Ability to quickly synthesize thoughts and organize information
- Openness to tackle any required project or task
- Strong communication skills
- Ability to work well with colleagues across multiple teams and regions
- Fluency in English
- Fluency in Turkish
Tasks
- Support building supply and demand models for agricultural commodities.
- Support building new analytical models.
- Support developing efficient processes based on best practices.
- Analyze short-term market developments for trade ideas.
- Manage desk data flows.
- Onboard new datasets.
- Resolve data flow issues.
- Run and maintain fundamental data processes.
- Capture cross-desk synergies (equity mapping) with teams.
- Improve systematic reporting (callouts) of information flow.
- Provide ad hoc organizational and technical support.
- Verify model and visualization functionality.
- Check for data issues.
- Maintain up-to-date team Confluence pages.
- Produce ad hoc analysis for traders and analysts.
- Build market-leading analytical models via long-term projects.
Work Experience
- approx. 1 - 4 years
Education
- Master's degree
Languages
- English – Business Fluent
- Turkish – Business Fluent
Tools & Technologies
- Python
- Excel
- VBA
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Commodities Fundamental Analyst(m/w/x)
Building supply/demand models for agricultural commodities, analyzing market developments for trade ideas. Advanced degree in Math/Stats/Quant Finance and Python coding skill required. Exposure to systematic trading strategies, direct impact on market decisions.
Requirements
- Advanced degrees (MSc preferred) in Mathematics/Statistics or Quantitative Finance
- Experience in quantitative research (ideally through prior internship or related position, especially in commodities trading)
- Experience in highly quantitative trading asset classes (power) and systematic trading (plus)
- Python coding skill (required)
- Ease with Excel/VBA (plus)
- Passion for investing and commodities market trends
- Excellent writing skills
- Ability to quickly synthesize thoughts and organize information
- Openness to tackle any required project or task
- Strong communication skills
- Ability to work well with colleagues across multiple teams and regions
- Fluency in English
- Fluency in Turkish
Tasks
- Support building supply and demand models for agricultural commodities.
- Support building new analytical models.
- Support developing efficient processes based on best practices.
- Analyze short-term market developments for trade ideas.
- Manage desk data flows.
- Onboard new datasets.
- Resolve data flow issues.
- Run and maintain fundamental data processes.
- Capture cross-desk synergies (equity mapping) with teams.
- Improve systematic reporting (callouts) of information flow.
- Provide ad hoc organizational and technical support.
- Verify model and visualization functionality.
- Check for data issues.
- Maintain up-to-date team Confluence pages.
- Produce ad hoc analysis for traders and analysts.
- Build market-leading analytical models via long-term projects.
Work Experience
- approx. 1 - 4 years
Education
- Master's degree
Languages
- English – Business Fluent
- Turkish – Business Fluent
Tools & Technologies
- Python
- Excel
- VBA
About the Company
Squarepoint Capital
Industry
Agriculture
Description
Squarepoint Capital focuses on investment and trading strategies, leveraging advanced quantitative methods and technology to drive financial performance.
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