Develop complex predictive and optimization models and forecasting solutions from conception to implementation using applied Artificial Intelligence/Machine Learning (AI/ML) platforms, such as Amazon SageMaker, SAP IBP, and a custom time series forecasting framework.

Specific job duties include:

(1) develop complex proofs of concept, minimum viable products, and fully deployable forecasting solutions within the global food supply chain domain, including regression analysis, time series models, and probabilistic models;

(2) lead the design and enhancement of new modeling features and algorithmic capabilities for designated AI/ML platforms, supporting end-to-end supply chain and demand planning optimization;

(3) provide technical leadership and thought partnership across use cases, including demand forecasting for food products such as protein, salt, cocoa, and oils across various global geographies;

(4) manage data science initiatives in food supply chain planning, including scoping, development, deployment, and monitoring of machine learning models using Machine Learning Operations (MLOps) best practices;

(5) mentor junior team members and serve as a technical resource for cross-functional stakeholders while aligning project work with strategic business objectives;

(6) collaborate with cross-functional teams including product owners, engineers, data scientists, and supply chain planners to deliver scalable, production-ready solutions;

(7) assess completeness and reliability of global supply chain data using reconciliation logic, anomaly detection, and validation frameworks;

(8) conduct data mining and audit analytics to uncover demand signals, seasonal patterns, and historical trends;

(9) apply statistical modeling, machine learning, and natural language processing (NLP) to derive insights from structured and unstructured datasets;

(10) develop and deploy forecasting and optimization models to support global demand prediction, inventory alignment, and production planning;

(11) clean, transform, and manipulate supply chain data using programming languages and statistical tools, such as Python, R, and SAS;

(12) build performance dashboards and visualizations using Tableau, Power BI, and Excel to communicate insights to technical and business stakeholders;

(13) design and implement a scalable, AI/ML-driven time series forecasting framework using AWS infrastructure, Amazon SageMaker, and sktime libraries to deliver automated and accurate forecasts;

(14) incorporate key components such as exploratory data analysis (EDA), outlier correction, stationarity testing, changepoint detection, clustering, Fourier-based seasonality analysis, preprocessing, and feature engineering;

(15) develop infrastructure for parallelized model deployment, automated retraining, and performance monitoring with integrated version control and model tracking;

(16) integrate the forecasting framework with enterprise-wide Integrated Business Planning (IBP) systems to enable dynamic infrastructure tuning or generation of standalone forecasts;

(17) follow design principles including reproducibility, modularity, measurability, scalability, discoverability, and extensibility to ensure long-term adaptability, efficiency, and trust;

(18) use Python and R prototyping languages and Java programming language. Uses the following tools and technologies: Amazon SageMaker and AWS; time series modeling and statistical libraries including sktime, prophet, ARIMA, ETS, Croston, ThetaForecaster, AutoETS, AutoARIMA, and ExponentialSmoothing; machine learning libraries including xgboost, lightgbm, scikit-learn, and optuna; distribution fitting and changepoint detection tools such as fitter, ruptures, and pwlf; advanced feature engineering using FourierFeatures, HolidayFeatures, DateTimeFeatures, and WindowSummarizer; data processing libraries including pandas, numpy, scipy, and statsmodels; visualization tools.

Full time employment, Monday - Friday, 40 hours per week, $148,700.24 per year.

At Cargill we put people first. As part of your overall rewards, we offer a comprehensive benefit program including medical and/or other benefits dependent on the position offered and hours worked. Visit: https://www.cargill.com/page/my-health/mh-health-and-wellness to learn more (subject to certain collective bargaining agreements for Union positions).

MINIMUM REQUIREMENTS:

This position requires a Bachelor's degree or equivalent in Data Science, Electronic Engineering, Business Analytics, or a related field, and 5 years related (progressive, post-baccalaureate) experience in a data science or data analyst related occupation.

Must also have 24 months of experience with each of the following:

• Using AI/ML, including in creating regression analysis, time series, and probabilistic models.
• Using Python and R prototyping languages and Java programming language.
• Creating data performance reporting and visualization templates using Tableau and Excel.
• Working with predictive models for supply chain solutions.
• Using forecasting timeseries, ARIMA, Prophet, or DeepAR.

Employer will accept experience gained concurrently.