Bunge Limited (www.bunge.com, NYSE: BG) is a leading global agribusiness and food company operating in over 40 countries with approximately 32,000 employees. Bunge buys, sells, stores and transports oilseeds and grains to serve customers worldwide; processes oilseeds to make protein meal for animal feed; produces edible oil products for consumers and commercial customers in the food processing, industrial and artisanal bakery, confectionery, human nutrition and food service categories; produces sugar and ethanol from sugarcane; mills wheat, corn and rice to make ingredients used by food companies; and sells fertilizer in South America. Founded in 1818, the company is headquartered in White Plains, New York.
The data scientist will be an integral part of the Bunge Economic Analysis team analyzing large Bunge internal and publicly available data sets and developing advanced modelling techniques using best practices in Machine Learning for advancing the Global economic research functions in forecasting market dynamics inclusive of crop production, pricing and customer behavioral analysis globally.
Work in a cross-disciplinary project team of database specialists, data scientists, and business subject-matter experts.
Gain in-depth understanding of business problems from subject-matter expects and identify and analyze the relevant variables that affect global commodity markets and their components;
Translate business problems into data-driven analytics / machine-learning tasks and swiftly develop and deploy high-performance and resilient machine learning based solutions.
Develop predictive models using machine learning, statistical and econometric tools.
Monitor the performance of machine learning based solutions to ensure business impact.
Design strategies and implement algorithms to analyze and leverage data, assessing the effectiveness and accuracy of data sources to be used as inputs to developing global models.
Present findings to a large group of business users; effectively summarize and communicate results to the global group for risk management.
Minimum MS degree in a quantitative field (physics, statistics, engineering, computer science, math, econometrics, etc.).
3+ years of research or industry experience in machine learning, pattern recognition, time series analysis, deep learning, and related data-driven fields.
Expertise in analytical packages such as Python, R, C/C++, PyTorch, or Tenserflow.
Intellectually curious and creative, willing to share knowledge, and adaptive to new techniques.
Strong communication skills, critical thinking, attention to detail, and business acumen.
Solid foundation in mathematics and statistical modeling to be able to solve complex business problems via statistical models, machine learning algorithms, text analytics/NLP etc.
Direct industry or educational experience in agricultural economics.
Understanding of agronomy, weather, remote sensing, GIS, economics, and finance
Publication on top journals and conferences
Experience with large-scale database and distributed computing
Participation in open source community
Bunge is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, citizenship, age, disability or military or veteran status, or any other legally protected status. Bunge is an Equal Opportunity Employer. Minorities/Women/Veterans/Disabled