Forecasting Data Scientist

Overview

Forecasting Data Scientist role at Mondelēz International. You will help the business react to changing conditions with data analysis, define requirements, perform analysis, and identify patterns in large data sets.

• Lead statistical forecasting process to provide a statistical base forecast for demand planning.
• Lead continuous improvement projects to create more efficient, robust, and accurate models for prediction.
• Analyze business requirements to guide data modeling and apply data analysis, design, modeling, and quality assurance techniques to establish or modify data structures and related components.
• Manage iteration, review, and maintenance of data requirements and data models; assist in creating the semantic layer of data.
• Choose suitable data modeling approaches and build flexible data models that adapt to changing business requirements.
• Reconcile multiple logical source models into a single, consistent model following data architecture guidelines.
• Design, build, and maintain Python/PySpark algorithms for predictive analysis to improve planning processes.
• Analyze code and implement strategies for more accurate and efficient results.

• Experience in data modeling within a large, complex business with multiple systems.
• Ability to simplify complex problems and communicate them to a broad audience.
• Experience designing, building, implementing, and/or maintaining Python/PySpark algorithms for predictive analysis to improve planning processes.
• Ability to work in cloud environments with tools like Databricks and promote best practices.
• Experience aligning and coordinating activities with different areas and stakeholders to ensure project execution.

• The Data Scientist will be responsible for advanced forecasting methodologies for demand forecasting to improve accuracy and bias.
• Determine, create, and maintain best statistical models considering SKU demand behavior using segmentation to generate high-quality demand forecasts with low error and bias.
• Refine forecasting models by reviewing performance and incorporating feedback from Demand Planners.
• Analyze model performance on a monthly/weekly basis, post-process outputs, and finetune as required.
• Propose strategies to enhance code efficiency and accuracy in Databricks.
• Collaborate with Demand Planners to explain model results and gather feedback to improve models.
• Lead, develop, and deploy algorithms on Databricks to improve predictive processes.

• Bachelor's Degree required. Master’s in Statistics, Applied Mathematics, or Engineering with analytics coursework preferred.
• Certifications in Google Cloud Platform (Data Scientist/Data Analyst) or Databricks preferred.

• 10+ years of experience leading multiple supply chain and forecasting projects with teams.
• Experience in FMCG/Retail/related industry data and understanding of business processes (preferred).
• Ability to articulate data science outcomes in business terms.
• Experience leading projects and/or processes.
• Fluent English.
• Proficient in Python (preferred), PySpark (preferred), R, or Julia.
• Experience developing and deploying statistical or machine learning solutions.
• Knowledge of data science cloud platforms like Databricks (preferred).

This is a hybrid role – three days onsite at East Hanover, NJ. No option for 100% remote.

Base salary range: $83,800 to $115,225, plus eligibility for a bonus program based on performance and company results.

Benefits include health insurance, wellness and family support, life and disability insurance, retirement plans, paid leave, education programs, and paid holidays/vacation. Some benefits have eligibility requirements. No relocation support available.

The United States is Mondelēz International’s largest market, with a significant employee and manufacturing footprint. We produce beloved brands and have offices, sales, manufacturing, and distribution locations nationwide.

Mondelēz Global LLC is an Equal Opportunity/Affirmative Action employer. All qualified applicants will be considered without regard to protected characteristics or status. Accommodation is available upon request.

• Regular
• Data Science
• Analytics & Data Science