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Knowledge Graph Engineer

WPP · Copenhagen, Denmark · по договорённости

Компания
WPP
Город
Copenhagen, Denmark
Зарплата
по договорённости
Уровень
middle
Формат
full_time
Иностранная компания
нанимает русскоязычных

WPP is the trusted growth partner for the world’s leading brands.

We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com.

Why we're hiring:

About Data & Technology Solutions

WPP’s Data & Technology Solutions is the WPP’s unified global data products and technology team. We work with our agencies and clients to build data data-driven solutions and technology product to power marketing transformation.

WPP Open is our AI platform for marketing, it connects marketing professionals, data, tools and AI in a single place. WPP Open is the simplest, safest and fastest way to realize the benefits of scaled AI – delivering better-informed creative ideas faster, at scale and at lower cost.

We’re endlessly curious and our team of thinkers, builders, creators and problem solvers are over 2,000 strong, across 20 markets around the world.

What you'll be doing:

Work with development teams to effectively use the existing Knowledge Graph

Translate product and business requirements into graph-based data solutions

Extend and adapt schemas in collaboration with architects when needed

Ensure data consistency and correct usage patterns across applications

GRAPH MACHINE LEARNING & AI INTEGRATION

Develop graph-based ML models: node embeddings, link prediction, and GNNs

Integrate knowledge graphs with AI/LLM-driven applications

Build solutions for semantic search, entity resolution, and recommendation systems

BACKEND SYSTEMS & APIS

Build and maintain high-performance APIs for graph-powered services

Collaborate with engineering to design scalable, production-grade systems

Optimize processing and querying of large datasets

DATA STRATEGY & INNOVATION

Identify opportunities to leverage graph intelligence for marketing technology

Partner with cross-functional teams to translate business problems into graph-based solutions

Drive innovation in AI, semantic technologies, and AdTech applications

KNOWLEDGE SHARING

Support engineers in understanding how to use the graph effectively

Participate in technical discussions and solution design

Contribute to documentation and usage guidelines

What you'll need:

We are seeking a highly skilled and experienced Knowledge Graph Expert with Data Scientist mindset to join our Data & Technology Solutions team. This individual will play a critical role in designing, building, and scaling enterprise-grade knowledge graph systems that power next-generation marketing intelligence, including the WPP Open AI platform.

If you are passionate about graph data modelling, semantic technologies, AI-driven insights, and building high-performance backend systems for large-scale marketing ecosystems, we would love to hear from you.

You have:

Experience working with existing Knowledge Graphs in production environments

Understanding of data modelling concepts and entity relationships (not necessarily designing from scratch)

Hands-on experience querying graph databases

Working knowledge of graph query languages such as Cypher or SPARQL

Familiarity with semantic data concepts (RDF/OWL or similar — practical level)

General understanding of machine learning concepts

Interest in graph analytics or applied graph ML (e.g., recommendations, similarity, traversal-based features)

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