Raihlah apa yang akan datang.
Ciptakan peluang peluang baru.

Job Purpose and Impact

As Senior Professional, AI & Data Science , you will drive the development and deployment of advanced pricing solutions using cutting-edge machine learning and AI. You will leverage diverse data sources to create scalable, predictive models that directly influence business strategy and pricing decisions across Cargill’s global operations. You will collaborate with product managers, pricing execution teams, and commercial stakeholders to enable value-based pricing through innovative ML prototypes.

Key Accountabilities

• Design and Deploy ML Models: Implement pricing models to capture fundamental and non-fundamental factors in protein, food ingredient, and commodity markets.
• Monitor and Optimize: Conduct benchmarking, back testing, and performance evaluation using real-time data and feedback loops to ensure model accuracy.
• Explain and Adapt: Partner with pricing teams to validate proper model application and identify opportunities for continuous refinement.
• Data Product SME: Collaborate with software development teams to design user-friendly pricing tools and dashboards for business-end users.
• Scalable Infrastructure: Develop ML components that generalize across different product categories and external data sources to remain robust in dynamic markets.
• Trend Integration: Stay current with emerging developments in GenAI, ML, and pricing strategy to integrate new techniques into existing practices.

Qualifications

• Bachelor’s degree in Data Science, Mathematics, Econometrics, Engineering, Statistics, Economics, Quantitative Finance, or a related quantitative field.
• Minimum of 4 years of relevant AI/ data science experience (or an advanced degree in a related field).
• Strong programming skills in Python with proficiency in libraries such as Pandas, NumPy, and scikit-learn.
• Deep knowledge of statistical analysis, hypothesis testing, and data-driven decision-making.
• Proven experience building, training, and validating ML models, including regression, classification, time series forecasting, and recommendation systems.