Forecasting Data Scientist

Job Description

Are You Ready to Make It Happen at Mondelēz International?

Join our Mission to Lead the Future of Snacking. Make It With Pride.

You will help our business react to changing business conditions with excellent data analysis. You will define the requirements, perform the analysis and identify patterns in large amounts of data.

How you will contribute

You will:

• Lead statistical forecasting process to provide business a statistical base forecast for its demand planning process.

• Lead some continuous improvement projects to get a more efficient, robust, and accurate models to predict.

• Analyze business requirements as a guide for data modeling and apply data analysis, design, modeling, and quality assurance techniques, based on a detailed understanding of business processes, to establish, modify or maintain data structures and associated components (entity descriptions, relationship descriptions, attribute definitions

• Manage the iteration, review and maintenance of data requirements and data models and you will assist in creating the sematic layer of data

• Choose a suitable data modeling approach for each project, such as by assessing the suitability of existing data models and build data models with the flexibility to change when business requirements change

• Reconcile multiple logical source models into a single, logically consistent model and you will ensure that the proposed model follows data architecture guidelines and best practices

• Design, build, implement and/or maintain Python/PySpark algorithms to execute predictive analysis which help to improve planning processes.  

• Analyse code, define and implement strategies to have more accurate and efficient results

What you will bring

A desire to drive your future and accelerate your career and the following experience and knowledge:

• Extensive experience in data modeling in a large complex business with multiple systems
• Ability to simplify complex problems and communicate them to a broad audience
• Design, build, implement and/or maintain Python/PySpark algorithms to execute predictive analysis which help to improve planning processes. 
• Analyze code, define, and implement strategies to have more accurate and efficient results
• Working in cloud computing environments with tools like databricks and help MDLZ to have better practices on it.
• Aligning and coordinating activities with different areas and stakeholder to guarantee a good execution of projects and processes.

What you need to know about this position:

The Data Scientist will be responsible for advanced forecasting methodologies for demand forecasting to generate better forecasting results in terms of accuracy and bias

• Determine, create and maintain the best Statistical models be to be used, by considering SKU demand behavior using segmentation strategy, to generate high quality demand statistical forecast with low forecast error and bias

• Refine forecasting models, by reviewing forecast performance and incorporating feedback from the Demand Planner, to improve forecast error and bias metrics

• Analyze the model performance every month / week where MAPE (Main Absolute Percentage Error) is deteriorating and post process the output and if required finetune the output

• Propose additional strategies to have a better code (efficient or more accurate) to execute in Databricks

• Collaborate with Demand Planners to provide explainability of models and gather feedback to improve the models 

• Lead, develop, and deploy some algorithms built on databricks that help to the predictive process to be more efficient and accurate

Education / Certifications:

• Bachelor's Degree required. Masters in quantitative field of Statistics, Applied Mathematics or Engineering, with specific full-time courses in Analytics preferred

• Certifications Google Cloud Platform as Data Scientist, or Data Analyst, or in Databricks preferred

Job specific requirements:

• 10+ years of experience in handling multiple projects leading in the domain of supply chain and forecasting with multiple team members as part of org structure

• Experience on working with FMCG, Food & Beverages, Retail or similar industry data with understanding the business process will be an advantage (nice to have)

• Should be able to articulate data science outcome into business understandable language

• Experience leading projects and/or processes