Overview / Brief
Louis Dreyfus Company is a leading merchant and processor of agricultural goods. Our activities span the entire value chain from farm to fork, across a broad range of business lines, we leverage our global reach and extensive asset network to serve our customers and consumers around the world. Structured as a matrix organization of six geographical regions and ten platforms, Louis Dreyfus Company is active in over 100 countries and employs approximately 18,000 people globally.
We are seeking a motivated and enthusiastic Junior Data Scientist to join our Palm Platform team. The ideal candidate will have a passion for agriculture and a thirst for learning new skills. As a Junior Data Scientist, you will play a key role in developing and applying analytical and machine learning solutions to tackle various agricultural challenges. You will have the opportunity to work with large spatial-temporal datasets, standard analytical packages, and financial instruments to support supply, demand, and marketing strategies. We are looking for someone who thrives on technology and innovation, excels at solving complex problems with creative solutions, and is adept at communicating findings to local and global stakeholders.
Diversity & Inclusion
LDC is driven by a set of shared values and high ethical standards
Diversity is part of our DNA. LDC strives to create a diverse and inclusive work environment where people can thrive regardless of gender, sexuality, ethnicity or background.
Sustainability
Sustainable value is at the heart of our purpose as a company
We are passionate about creating fair and sustainable value, both for our business and for other value chain stakeholders: our people, our business partners, the communities we touch and the environment around us.
Main Responsibilities:
- Develop predictive models:
- Use statistical, econometric, and machine learning tools to analyze large-scale internal and public commodity-related data. This includes estimating supply, demand, and price models based on sound theory, and best-practice programming techniques.
- Create dashboards and custom tools:
- Develop dashboards and custom tools to deploy findings to commercial groups using latest tools and technologies.
- Present findings:
- oPresent findings to broad commercial groups and effectively summarize and communicate model features and results for global risk management.
- Contribute to database construction:
- Contribute to the construction and maintenance of internal databases and Python libraries.
- Build high-quality models:
- Build high-quality statistical, economic, and machine learning models on demand using state-of-the-art analytical tools. Clearly explain assumptions, model advantages, and limitations.
Experiences & Competencies:
- Knowledge of statistical methods and machine learning techniques, with practical experience applying them to real-world agricultural problems
- Know how to communicate/explain complex ideas in a simple way to non-technical stakeholders
- Good time management skills and ability to manage multiple tasks and work to deadlines
- Interpersonal skills, ability to forge relationships with colleagues and external contacts
- Ability to work within a complex and international environment
- Genuine interest in global economics and commodities markets
Technical Skills:
- Advanced IT skills (e.g., Excel, VBA, PowerPivot, Power Query)
- Good Programming skills (Python, etc.) and experience with data analysis libraries (e.g., Pandas, NumPy, SciPy, GeoPandas, etc.)
- Strong command on SQL and Data visualization tools
- Good Business Intelligence awareness
Language:
Academics:
- Degree in Computer Sciences, Statistics, or Mathematics, or related field of study
