The Data Scientist leverages advanced data science, machine learning, and Generative AI (GenAI) capabilities to generate insights, improve decision-making, and drive innovation across the organization. This role plays a critical part in identifying, designing, and integrating AI-powered solutions into business processes. The Data Scientist works closely with AI Data Engineers, software engineers, and business stakeholders to develop, deploy, and scale AI models into production-grade applications, ensuring responsible, trustworthy, and seamless AI adoption across the Carlsberg (CB) landscape.
Personal qualifications / competencies:
Core Technical Skills Strong analytical and problem-solving skills Strong Python proficiency, including:
o Data pre- and post-processing
o Pipeline development and optimization
o API integrations
o Optimization techniques (e.g., PuLP)
o Basic testing and code quality practices Proven experience in data science, statistical modeling, and machine learning Hands-on experience with ML and data libraries such as Scikit-learn, XGBoost, PyTorch, TensorFlow, Pandas, NumPy Experience preprocessing and optimizing structured and unstructured datasets to make them LLM-ready Experience with GenAI and agentic frameworks, including:
o Prompt engineering o RAG (Retrieval-Augmented Generation)
o Multi-agent systems o MCP servers o Frameworks such as Autogen and OpenAI API integrations Data & Platform Skills Working knowledge of SQL (e.g., SELECT, JOIN, GROUP BY) and familiarity with NoSQL concepts
Experience with data pipelines, ETL/ELT processes, and orchestration tools (experience with Microsoft Fabric is a strong plus) Familiarity with MLOps practices, including model deployment, monitoring, and lifecycle management Hands-on experience with cloud platforms, preferably Azure, including:
o Azure AI services o Azure AI Foundry o Copilot Studio o Data storage solutions such as Blob Storage and PostgreSQL Familiarity with standard development tools and practices, including Git Visualization & Communication Experience with data visualization and storytelling using tools such as Power BI, Tableau, or Python-based dashboards (Dash, Streamlit) Strong ability to translate business problems into analytical and AI-driven solutions Fluent English communication skills, both written and verbal Architecture & Responsible AI Ability to define integration points across products to ensure end-to-end application flow Commitment to building responsible, trustworthy, and ethical AI solutions within the CB landscape
Masters degree in Data Science, Statistics, Mathematics, Computer Science, or a related field Relevant certifications in machine learning, analytics, or cloud platforms are advantageous Job responsibilities: Identify opportunities to apply data science and GenAI across business functions Develop and deploy predictive and prescriptive models for use cases across Carlsberg commercial, supply chain, and operations Work with large datasets to clean, analyze, and visualize trends, patterns, and drivers Collaborate with business stakeholders to frame problems and deliver data-driven insights Deploy AI/ML models into production and monitor performance over time Work closely with AI Data Engineers and software teams to integrate models into AI-driven applications Document methodologies, architectures, and results for both technical and non-technical audiences Contribute to the scaling of AI and GenAI capabilities across the organization Required Leadership behaviors: Alignment
- Frames data science work around key business priorities
- Collaborates with stakeholders to ensure adoption and impact
Accountability
- Delivers analytical solutions with measurable business outcomes
- Demonstrates rigor in experimentation and model evaluation
Action
- Proactively explores data for insights and opportunities
- Applies creativity and critical thinking to solve business problems
