Senior Data Scientist

Senior Data Scientist

The mission of Global Analytics is to lead HEINEKEN into becoming a data-driven company and the best-connected brewer. As a team, we radiate a data-driven entrepreneurial culture to the rest of the company. We act as an incubator for smart data products in all business areas, from sales to logistics and marketing to purchasing. This approach has allowed us to grow rapidly and launch many valuecreating use cases from the management of spare parts to the allocation of media spending. Our focus for the upcoming year is to scale these, and other, use cases to as many countries as possible globally.

Key Responsibilities:

• Perform advanced time series analysis to understand and predict demand, sales, and other key business metrics.
• Develop, implement, and maintain real-time data solutions to drive informed decision making.
• Build and refine predictive models to improve forecasting accuracy, inventory management, and production planning.
• Collaborate with cross-functional teams to understand business needs and translate them into data-driven solutions.
• Work with large datasets, using programming languages such as Python, R, or others, to extract, transform, and analyze data.
• Design and implement data visualization tools to communicate insights effectively to various stakeholders.
• Maintain up-to-date knowledge of emerging data science and machine learning techniques and apply them to business problems.
• Promote data-driven decision-making culture within the organization.

Qualifications

• 7+ years of professional experience in data science with a focus on time series analysis and real-time data projects.
• Strong understanding of underlying models and algorithms used in time series forecasting, such as ARIMA, Exponential Smoothing, and machine learning approaches.
• Proficiency in data analysis and machine learning tools and libraries, such as Python, R, TensorFlow, or PyTorch.
• Experience with big data technologies and distributed computing (e.g., Hadoop, Spark).
• Ability to work effectively in a multicultural team and adapt to various working styles and perspectives.
• Excellent communication and data visualization skills to convey complex findings to both technical and non-technical stakeholders.
• Proven problem-solving skills and a strong analytical mindset.
• Familiarity with data engineering and full-stack data science is a plus