As a value-obsessed team and organisation, the AME Analytics Hub is expanding its capabilities by creating a team focussed on experimentation and causal studies to determine the effectiveness of both analytic and non-analytics initiatives across the entire HEINEKEN company.
We are looking for 2x Data Scientists to support the vision and strategies that will provide crucial information to the organisation. This is a high-impact role that will help to inform the future direction of the organisation. The ideal candidate will excel in causal studies and experimental design, cross-functional and cross-domain collaboration and share a passion for enabling scaling solutions to continuously improve.
If these challenges sound interesting and exciting, we hope you apply. We want to be collaborative, innovative, and reliable. We see collaboration as key in our global community with many different cultures, roles, and challenges. And strive to create an environment where you enjoy both the problems you are solving, but also the people you are solving them with. We innovate to transform HEINEKEN from a traditional to a data-driven company. We position ourselves as a business partner driving value creating decisions and building trust in our solutions.
In this role, you will:
- Be a strong thought partner influencing strategic decision-making through data-driven insights and recommendations.
- Effectively identify and apply analytics, experimentation, and causal inference techniques for business problems.
- Design experiments and pioneer methodologies to measure the value of company initiatives globally.
- Develop and validate the appropriate metrics to measure success in a given area.
- Cultivate strong partnerships with cross-functional partners from engineering, data science, analytics translators, etc.
- Cultivate strong partnerships with cross-functional partners from Global Analytics, Analytics Hubs and various Operating Companies within Heineken globally.
- Present outcomes of analysis to all levels of the company.
- A statistical expert with strong statistical knowledge and intuition, ideally applied in experimentation and observational causal studies settings.
- Proficient in Python and PySpark.
- Skilled in SQL and familiar with distributed data stores like Hive and Spark.
- Impact-driven, pragmatic and able to incorporate business context into data questions.
- Comfortable with ambiguity, thriving with minimal oversight and navigating complex processes and data landscapes.
- Excellent at communication. Able to convey technical content to non-technical audiences.
- Collaborative and thrive in team settings.
- Plus: A background in economics, econometrics.
- Plus: Familiar with software engineering practices.
- Plus: Familiar with Databricks