Posted:2 weeks ago|
Platform:
On-site
Full Time
About the Team
At Global Analytics, we’re driving HEINEKEN’s transformation into the world’s leading data-driven brewer. Our innovative spirit flows through the entire company, promoting a data-first approach in every aspect of our business. From sales and logistics to marketing and purchasing, our smart data products have been instrumental in accelerating our growth and operational excellence. The Global Analytics team is a diverse group of Data Scientists, Data Engineers, Business Intelligence Specialists, and Analytics Translators, spanning multiple countries and regions. Our culture fosters collaboration, innovation, and reliability. Together, we are committed to transforming HEINEKEN into a leader in data-driven decision-making, leveraging our global diversity to tackle challenges and create value.
Design and manage full-stack data science solutions from ingestion and transformation (ETL/ELT) through deployment and monitoring. Partner with marketing, product, and business stakeholders to align analytics with brand objectives and consumer insights. Translate ambiguous requirements into actionable data science tasks with measurable business impact.
· Advanced Analytics & Machine Learning
Develop and deploy ML models for predictive analytics, segmentation, personalization, recommendation systems, and time-series forecasting. Integrate brand performance metrics (awareness, consideration, trial, repeat purchase, market share) into ML pipelines. Apply cutting-edge techniques (Bayesian methods, reinforcement learning, optimization/metaheuristics) when needed.
· Brand Power & Market Insights
Build models that enhance customer journey mapping and improve product experience across channels. Develop insights into consumer sentiment, brand health, and market reach using structured and unstructured data. Monitor KPIs tied to brand strength such as brand awareness, customer loyalty, NPS, and sales uplift. Partner with marketing to design data-driven campaigns that strengthen brand equity.
Follow OOP principles in Python with clean, maintainable code. Implement CI/CD pipelines and orchestration (Kubernetes) for scalable ML operations. Manage cost and performance across cloud environments (Azure preferred, AWS/GCP acceptable).
· Visualization & Storytelling
Build brand-performance dashboards and data apps (Streamlit, Power BI, Plotly Dash) for executives and marketing teams. Present actionable insights in compelling, easy-to-understand formats tailored to brand, sales, and product stakeholders.
· Experience - 10+ years in data science, with at least 3–4 years in senior or leadership roles delivering end-to-end data products.
· Technical Skills- Strong Python (OOP, design patterns, NumPy, pandas, scikit-learn, TensorFlow/PyTorch). Cloud experience (Azure preferred, AWS/GCP acceptable). Experience with real-time data streaming (Kafka/Spark Streaming) and large-scale processing (Spark/Dask). Proficiency with version control (Git), CI/CD, and ML deployment pipelines.
· Domain & Brand Power Skills
Strong knowledge of brand health metrics, customer/product experience analytics, and marketing mix models. Deep understanding of consumer behavior, product reach, and market performance KPIs. Proven track record of applying data science to brand and business growth strategies.
· Soft Skills
Excellent communication, leadership, stakeholder management, and ability to tell a brand-driven story with data.
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