Demand Data Specialist

**Date**:Jul 1, 2025

**Location**: Sao Paulo, BR

**Company**:AkzoNobel

We are AkzoNobel. You probably know us.

We are present in homes, buildings, boats, cars—basically, on every surface where there is an opportunity to bring more color, life, and protection, in over 150 countries that use our paints and coatings. To continue painting a better future, we need you

We are looking for a Demand Data Specialist to work at our Morumbi office.

**Job Purpose**:
The primary objective of this role is to develop and maintain the most accurate and

effective statistical forecasting models for AkzoNobel’s key global business units

monthly. These models serve as the data-driven foundation for the Demand Plan

(DMR) within the Integrated Business Planning (IBP) cycle.

As the cornerstone of the IBP Demand Planning process, the Statistical Forecast is

critical across all AkzoNobel business units. The Demand Hub is responsible for

generating and delivering statistical forecasts for approximately 60 Commercial Units

across 8 Business Units within the Decorative Paints and Coatings segments.

This role emphasizes continuous improvement and automation, with a strong focus on

enhancing key performance indicators, including Forecast Accuracy, Forecast Bias, and

Forecast Value Added (FVA).

**Responsibilities**:

- **Continuous Improvement**:
- CI Focal Point for Data Science + Statistics projects directly applied to Demand in Decorative Paints and Coatings business. Focus on Automation and KPI Results. Managing the projects, getting support from the team, delegating the tasks, and defining the priorities.
- Specialist Hands-On (managing 5 Commercial Units), understand the Stakeholders' needs.
- Ensure the connection between the technical world and the operation or business.
- Drive Change. Defining and deploying the process and guidelines with the COE connection.
- **Statistical Forecast**:
- Ensure the data quality that will be used as a Statistical Base Forecast. Reviewing and fine-tuning the parameters, settings, and configurations whenever necessary.
- Ensure the flow of activities and execution of established procedures for generating the monthly statistical forecast.
- Execute some operational procedures based on guided interactions.
- Adjustments on the Statistical Forecast based on important reports that contribute to specific actions: Tracking Signal, Forecast Value Added, Largest Error Contributors, Control Chart, and Top Volatilities.
- Backward testing different methods and statistical models at different calculation levels to obtain the best results, aligning with the demand team of each business unit.
- Aligning with Demand Planners and Managers on potential leading indicators (exogenous variables) containing a high correlation with sales history and how they could influence the forecast.
- **Communication with Demand Planning**:
- Consistent communication with stakeholders (demand planners, demand managers), to understand their needs, identify opportunities for improvement, propose solutions, monitor effectiveness, and align expectations with transparency.
- Identifying and removing Outliers together with the demand planning areas, ensuring it will be uploaded in our main tool, and the historical base will be cleaned up.
- Analysis of Outliers automatically identified by the statistical engine system.
- Mapping of Phase In/Out items, aligning with the demand areas to upload in the system.
- Conduct monthly meetings to align statistical forecasts with business units, results, and outlook, seasonality, trends, and levels. Explaining in detail the reasons for what is changing between cycles, updates considering the most recent results, or regarding improvements.
- **Forecast KPI Performance Analysis**:
- Focus on statistical forecasts of the most representative and most critical items based on the ABC/XYZ curve.
- Evaluate whether the results of the main KPIs meet expectations, Accuracy, BIAS, and FVA (Forecast Value Added), in Lag-1, Lag-3.
- Understand the reasons for Low performance, identify the root causes, and propose solutions and corrective actions to achieve the goals.

**Key Performance Indicators**
- Timely availability of the Statistical Forecast
- Forecast Accuracy and Bias
- Forecast Value Added (Statistical)

**Education**:

- Bachelor’s degrees in Math, Statistics, Engineering, or Data Science.

**Experience**:

- Solid experience as a Statistician and Data Scientist with a focus on demand forecasting (sales/consumption).
- Experience in a Lead/Coordinator position (competitive advantage).
- Experience with Demand Planning and Supply Chain (competitive advantage)

**Specific knowledge**:

- Experience and understanding of statistical modeling.
- High level of experience in Data Analysis tools and languages.
- Experience with the tools and technology below:
- Advanced Excel: ability to handle data, knowledge of statistical resources within Data Analysis, Solver, Macros, VBA (Desired)
- Azu