Staff Data Engineer

Job Description

Are you a talented and driven Data Scientist with expertise in machine learning and a passion for building robust pipelines for demand forecasting? We are seeking a skilled individual to join our dynamic team at Kraft Heinz. Join our team and make an impact by leveraging machine learning and demand forecasting to drive data-driven decisions and optimize our business operations.

What’s on the Menu?

As a Staff Data Scientist, you will be a technical leader on demand forecasting team.  You will design, build, and test statistical and machine learning models to accurately predict demand from our retailers.  Additionally, you will review the junior team members output to ensure best practices have been implemented.  The models you build will be deployed into a production setting where your models will drive value across all our brands.  You will provide updates and results to the business on the progress of your work while partnering with the business users to identify modeling opportunity areas.

Key Ingredients:

• Utilize your strong analytical skills and machine learning expertise to develop advanced time-series models for demand forecasting.
• Collaborate with cross-functional teams to identify and define business problems related to demand forecasting.
• Conduct exploratory data analysis and feature engineering to extract valuable insights from complex datasets.
• Work in tandem with the Global Data Science Lead and North America Lead to create a roadmap for EMEA Demand modeling
• Develop and implement machine learning algorithms to optimize demand forecasting accuracy and efficiency.
• Evaluate and fine-tune models by applying statistical methods and running experiments on real-world data.
• Monitor model performance and proactively identify opportunities for improvement and optimization.
• Communicate findings and insights to stakeholders in a clear and concise manner, both verbally and through data visualization techniques.
• Stay up-to-date with the latest advancements in machine learning and demand forecasting techniques, and apply them to enhance our forecasting capabilities.

Recipe for Success: Apply if it sounds like you!

• Master’s degree in Computer Science, Statistics, Mathematics, or a related field. PhD is a plus.
• 5+ years experience with predictive modeling time-series, machine learning, statistical modeling
• Experience building demand forecast models
• Proficiency in programming languages such as Python and R, as well as libraries like scikit-learn
• Solid understanding of data engineering principles
• Extensive knowledge on factors that influence shipment demand
• Proficient in SQL and working with relational databases.
• Experience using cloud-based services such as AWS, Azure, or Google Cloud
• Excellent problem-solving skills and ability to think critically about complex business challenges.

We hope to find you a seat at our table!

Location(s)

Amsterdam, London – The Shard

Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes.