Senior Data Scientist

About the role

Cargill is committed to providing food and agricultural solutions to nourish the world in a safe, responsible, and sustainable way. Sitting at the heart of the supply chain, we partner with farmers and customers to source, make and deliver products that are vital for living.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• Mentor junior team members and serve as a technical resource for cross-functional stakeholders while aligning project work with strategic business objectives.
• Collaborate with cross-functional teams including product owners, engineers, data scientists, and supply chain planners to deliver scalable, production-ready solutions.
• Assess completeness and reliability of global supply chain data using reconciliation logic, anomaly detection, and validation frameworks.
• Conduct data mining and audit analytics to uncover demand signals, seasonal patterns, and historical trends.
• Apply statistical modeling, machine learning, and natural language processing (NLP) to derive insights from structured and unstructured datasets.
• Develop and deploy forecasting and optimization models to support global demand prediction, inventory alignment, and production planning.
• Clean, transform, and manipulate supply chain data using programming languages and statistical tools, such as Python, R, and SAS.
• Build performance dashboards and visualizations using Tableau, Power BI, and Excel to communicate insights to technical and business stakeholders.
• 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.
• Incorporate key components such as exploratory data analysis (EDA), outlier correction, stationarity testing, changepoint detection, clustering, Fourier-based seasonality analysis, preprocessing, and feature engineering.
• Develop infrastructure for parallelized model deployment, automated retraining, and performance monitoring with integrated version control and model tracking.
• Integrate the forecasting framework with enterprise-wide Integrated Business Planning (IBP) systems to enable dynamic infrastructure tuning or generation of standalone forecasts.
• Follow design principles including reproducibility, modularity, measurability, scalability, discoverability, and extensibility to ensure long-term adaptability, efficiency, and trust.
• 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.

Requirements

• 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.

Qualifications

• Experience with Amazon SageMaker, SAP IBP, and custom time series forecasting framework.
• Experience with Python, R, and Java programming languages.
• Experience with Tableau, Power BI, and Excel for data performance reporting and visualization.
• Experience with predictive models for supply chain solutions.
• Experience with forecasting timeseries, ARIMA, Prophet, or DeepAR.

Skills

• Applied Artificial Intelligence/Machine Learning (AI/ML)
• Python and R prototyping languages
• Java programming language
• Data performance reporting and visualization
• Predictive models for supply chain solutions
• Forecasting timeseries, ARIMA, Prophet, or DeepAR

Benefits

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

Pay

$148,700.24 per year.

Schedule

Monday – Friday, 40 hours per week.

Benefits

Visit: https://www.cargill.com/page/my-health/mh-health-and-wellness to learn more (subject to certain collective bargaining agreements for Union positions).

Equal Opportunity Employer

Equal Opportunity Employer, including Disability/Vet.

LinkedIn Job Matcher

Find where you fit in at Cargill. Log in to connect your LinkedIn profile and we’ll use your skills and experience to search the jobs that might be right for you.

Diversity, Equity & Inclusion

Our inclusive culture helps us shape the future of the world.

Annual Report

Read Cargill’s Annual Report to see how we’re helping transform food and agriculture to build a food-secure world.