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São Paulo, Brazil
Actively hiring, first seen by us 6 days agoEmployment type in the employer’s posting: Part timeFrom the employer’s posting
Design and operationalize forecasts for cocoa supply, demand and prices
Implement model monitoring to catch forecast drift and performance decline
Partner with procurement, supply chain, finance and trading teams on decisions
Document models, logic and performance metrics
Explore GenAI tools for market intelligence and unstructured commodity reports
Design, develop, and operationalize advanced forecasting models for cocoa market dynamics including supply availability, demand planning, and price forecasting.
Implement model monitoring frameworks for early detection of forecast drift and performance degradation
Partner with procurement, supply chain planning, finance, and commodity trading teams to align model outputs with business decision-making.
maintain comprehensive documentation of models, logic, and performance metrics
Explore and apply GenAI capabilities (e.g., LLMs for market intelligence summarization, information retrieval from unstructured commodity reports)
Education / Certifications: - Education: Bachelor’s degree in a Quantitative Discipline (Economics, Statistics, Mathematics, Operations Research, or STEM field). Master’s preferred. - Experience: Minimum 3 years of data science/AI experience, with a strong focus on forecasting and/or supply chain analytics.
Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 6
Similar jobs usually come down between day 5 and day 41.
From 10,578 similar postings that came down. Coming down is not always a hire.
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- Knowledge of Indicators (KPI's) and scorecards - Knowledge of BI tools like Tableau, Excel, Alteryx, R, Python, etc. is a plus More about this role
Programming Python, PySpark, SQL. MLOps
We are seeking a skilled and motivated Data Scientist to support the Cocoa Enterprise Program – a strategic initiative focused on cocoa supply chain strategy, forecasting, and scenario planning. The successful candidate will play a pivotal role in developing, maintaining, and enhancing forecasting models that inform cocoa sourcing strategy, pricing decisions, and supply chain planning across the enterprise. This role operates within Mondelēz’s internal data science ecosystem (Databricks, cloud platforms). Beyond technical expertise, the ability to translate complex model outputs into actionable strategy recommendations will be key to success. What you need to know about this position:
MLOps Experience with model productionization, CI/CD pipelines, model monitoring, and lifecycle management (MLflow or equivalent). Statistical Foundations
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We file this job under Analyst, by the work the posting describes.
Analysts answer business questions with data. They pull numbers with SQL, build reports and dashboards, and explain what changed and why to the people making decisions.
Most postings ask for SQL, spreadsheets, a dashboard tool such as Tableau or Power BI, and clear writing.
Unlike a data scientist, an analyst mostly explains what happened rather than building models that predict what will.
Are You Ready to Make It Happen at Mondelēz International?
Join our Mission to Lead the Future of Snacking. Make It With Pride.
Together with analytics team leaders you will support our business with excellent data models to uncover trends that can drive long-term business results.
How you will contribute
You will:
What you will bring
A desire to drive your future and accelerate your career and the following experience and knowledge:
More about this role
We are aware of our role as transformation agents to generate positive change, so diversity, equity and inclusion are one of our priorities. We believe in breaking down stereotypes and barriers to ensure the representation of society within our company. And for that, we have a Diversity Committee that operates on four fronts, People with disabilities (PCD), Ethnic-Racial, Women and LGBTQIAP+, in addition to being part of MOVER – Movimento pela Equidade Racial.
We are seeking a skilled and motivated Data Scientist to support the Cocoa Enterprise Program – a strategic initiative focused on cocoa supply chain strategy, forecasting, and scenario planning. The successful candidate will play a pivotal role in developing, maintaining, and enhancing forecasting models that inform cocoa sourcing strategy, pricing decisions, and supply chain planning across the enterprise.
This role operates within Mondelēz’s internal data science ecosystem (Databricks, cloud platforms). Beyond technical expertise, the ability to translate complex model outputs into actionable strategy recommendations will be key to success.
What you need to know about this position:
Forecasting Model Development
Design, develop, and operationalize advanced forecasting models for cocoa market dynamics including supply availability, demand planning, and price forecasting. This product serves as an input into Mondelez’ scenario planning and optimization.
Platform Compliance & Model Deployment
Ensure all model integration and deployment activities comply with Mondelēz data science standards, including adherence to approved cloud architectures, MLOps practices, security protocols, and governance frameworks.
Cross-Functional Collaboration
Partner with procurement, supply chain planning, finance, and commodity trading teams to align model outputs with business decision-making.
Model Monitoring & Governance
Implement model monitoring frameworks for early detection of forecast drift and performance degradation; maintain comprehensive documentation of models, logic, and performance metrics.
GenAI & Advanced Analytics
Explore and apply GenAI capabilities (e.g., LLMs for market intelligence summarization, information retrieval from unstructured commodity reports) to enhance the program's analytical capabilities.
What extra ingredients you will bring:
Education / Certifications:
Job specific requirements:
Forecasting & Time Series
Experience with time series modeling (ARIMA, Prophet, exponential smoothing, state-space models), driver-based and causal modeling approaches (structural equation models, causal inference, Bayesian structural time series), ML-based forecasting (gradient boosting, neural networks), and deep learning approaches (LSTMs, Transformers).
Explainable AI
Experience with model interpretability and explainability techniques (SHAP, LIME, partial dependence plots, counterfactual explanations) to ensure model outputs are transparent and actionable for business stakeholders, particularly where models feed into scenario planning.
Programming
Python, PySpark, SQL.
MLOps
Experience with model productionization, CI/CD pipelines, model monitoring, and lifecycle management (MLflow or equivalent).
Statistical Foundations
Solid background in statistics, probability distributions, hypothesis testing, A/B testing, and multivariate analysis.
Communication
Ability to articulate complex model outputs and recommendations to leaders and non-technical stakeholders.
Mondelez International is attentive to the future of work and values the well-being of our people, seeking to provide the best experiences. Therefore, some of our administrative vacancies are eligible for the hybrid model, allowing remote work on certain days of the week.


No Relocation support availableBusiness Unit Summary
Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.
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São Paulo, Brazil
Ability to articulate complex model outputs and recommendations to leaders and non-technical stakeholders. Mondelez International is attentive to the future of work and values the well-being of our people, seeking to provide the best experiences. Therefore, some of our administrative vacancies are eligible for the hybrid model, allowing remote work on certain days of the week. 


No clear work-authorization passage found. Eligibility is unconfirmed.