Knowledge Graph

**ABOUT THE **OPERATIONS** **IT **TEAM**

Operations IT is a global IT capability supporting the Global Operations organisation. We business partner with Operations capability areas: Pharmaceutical Technology Development, Manufacturing & Global Engineering, Quality Control, Sustainability, Supply Chain, Logistics and Global External Sourcing and Procurement. We operate out of Operations hub sites including in the UK, Sweden, US, and China; and out of our Global Technology Centres in India and Mexico.

Here our work has a direct impact on patients - transforming our ability to develop life-changing medicines. We empower the business to perform at its peak and lead a new way of working, combining cutting-edge science with leading digital technology platforms and data. All with a passion to impact lives through data, analytics, AI, machine learning and more.

It’s a dynamic and challenging environment to work in - but that’s why we like it. There are countless opportunities to learn and grow, whether that’s exploring new technologies in hackathons, or transforming the roles and work of colleagues, forever. This is your chance to be part of a team that has the backing to innovate, disrupt an industry and change lives.

**THIS IS WHAT YOU’LL DO**

We are seeking an experienced Knowledge Graph & and Semantic Data EngineerLead to join our Data, Analytics & AI group for Operations IT. This group supports various business areas such as Develop, Manufacture, Supply Chain, Quality and Procurement with data-driven solutions and insights.

As a Knowledge Graph & Semantic Data Engineering Lead, **your role **is to **establish** and lead a Knowledge Graph and **s**S**emantic capability**. You’ll develop relationships with the business and start to create a backlog of use cases, in many circumstances you will need to educate the business on the value of sSemantics and Knowledge gGraphs.

In this role, you’ll contribute to the success of Operations by designing and implementing solutions involving graph and semantic technologies, as well as supporting our AI and Digital deliveries.

**Typical accountabilities** include**:
**Strat**egy**
- Provide strategy & Vision for Knowledge graph and semantic engineering:

- Partner with the AI team to develop a strategy for a Gen AI chatbot to query Operations data products via a knowledge graph.
- Guide the development, execution, and implementation of a roadmap for the strategies above.
- Collaborate with cross-functional teams and stakeholders to understand business requirements, identify knowledge gaps, and define data-driven strategies to inform decision-making and drive business growth.

**Knowledge Graph Platform**
- Leverage your expertise in graph databases and data engineering to design, develop, and mnaintainmaintain advanced knowledge-based systems and solutions that support our digital initiatives.
- Develop and implement advanced data engineering pipelines, including data ingestion, processing, storage, and analysis, ensuring the optimal performance, scalability, and reliability of our data infrastructure.
- Utilize your expertise in Graph DB and Graph query languages to continue developing and maintain existing data models and graph databases, enabling efficient querying and analysis of complex data relationships.
- Actively contribute to the continuous improvement of our knowledge engineering processes, tools, and methodologies, fostering a culture of innovation and excellence within the team.
- Stay abreast of emerging technologies and industry trends to continuously enhance the organization's Knowledge and semantic capabilities.

**Semantic Engineering**
- You will maintain, evolve, and grow our knowledge models (ontologies), presenting, selling them, annotate them to provide common understanding.
- Collaborate with cross-functional teams to define and document data models using ontological principles.
- Conduct ontology mapping and integration to facilitate data interoperability and integration across systems.
- Provide training and guidance to stakeholders on ontology usage and best practices for data organization.
- Stay updated on industry trends and advancements in ontology development to enhance data management processes.

**Stakeholder Collaboration**
- Collaborate with stakeholders across departments to understand requirements and ensure business needs are met.
- Act as a liaison between IT and Business Units, fostering strong communication and understanding.
- Oversight of partnerships with multiple third parties, academic or outsourced partners to shape and drive project outcomes and knowledge building.
- Delivering business education, improving awareness of KG capabilities, potential use-cases and key benefits within the wider business

**Quality Assurance**
- Implement and oversee robust quality assurance processes to ensure the accuracy, reliability, and security of data.
- Establish and monitor key performance indicators to measure the effect