At a Glance
- Tasks: Lead innovative knowledge engineering projects and develop cutting-edge AI solutions.
- Company: Join a global leader in technology consulting with a focus on innovation.
- Benefits: Competitive salary, diverse work environment, and opportunities for professional growth.
- Other info: Work in dynamic locations like London, Berlin, Madrid, or Paris.
- Why this job: Shape the future of AI and knowledge graphs while leading talented teams.
- Qualifications: Experience in Knowledge Graph technologies and strong leadership skills required.
The predicted salary is between 70000 - 90000 £ per year.
You lead the complete knowledge engineering scope on our most strategic and complex programs; lead creation of thought leadership, innovation, and assets for the discipline. You own how the most demanding programs formulate real-world problems into scalable AI and KG solutions, setting strategy and architecture end to end. You lead and develop teams of engineers, building capability across the discipline and guiding adoption of new methods and algorithms. You define what staying at the forefront means for the practice; drive innovation and translate it into new offerings. You set the standards for how ontologies are designed, evaluated, and maintained across programs. You make the case to senior stakeholders and shape the methodologies and data architectures that prove value at scale. You lead the creation of thought leadership, innovation, and reusable assets that advance the discipline beyond any single engagement. You partner with business and technical leaders to direct end-to-end delivery across complex, multi-stakeholder programs.
Work Lead the complete Knowledge Graph solution scope that transforms data architecture for our most strategic and complex clients. Own the design, development, and implementation of AI and semantic solutions across the program. Partner with project leaders, delivery leads, and senior client stakeholders to create stand-out, graph-powered offerings. Develop trusted-advisor relationships with senior client stakeholders. Make and defend the business case for the semantic layer solution at the executive level. Lead Accenture sales and pre-sales efforts and shape data transformation programs. Drive the practice's thought leadership, innovation, and asset development on trends and agentic technologies, and develop the teams who deliver them.
Basic (Required) Qualification
- Bachelor's degree or equivalent, plus all of the following:
- Significant experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL).
- Advanced practical knowledge of schema design, ontology management, and KG curation.
- Seasoned in designing and developing KG solutions and graph-based ML models (functional + technical).
- Proven experience in end-to-end data pipeline implementations for AI applications (esp. LLMs), with hands-on design and configuration.
- Extensive experience with strong knowledge of relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases.
- Managerial experience leading people, able to explain the value of the semantic layer and knowledge graphs to senior business and technology stakeholders, with a proven track record in sales and/or pre-sales and in delivering data transformation programs and developing teams.
Preferred Qualification
- Experience in practical NLP techniques and/or Search Techniques, prompt engineering.
- Experience with LLMs for enterprise-scale applications.
- Hands-on experience with cloud platforms (AWS, Azure, GCP).
- Well-versed in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g., Apache NiFi, Airflow).
- Strong collaboration skills with the ability to work across engineering, research, and product teams across multiple time zones.
- You have external client-facing consulting experience.
- Ph.D. in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.
- Broad experience in diverse ML techniques and agentic systems.
Locations
- London
- Berlin
- Madrid
- Paris
Knowledge Engineering Senior Manager/Associate Director employer: WeAreTechWomen
Accenture is an exceptional employer that fosters a culture of innovation and collaboration, particularly in the dynamic field of knowledge engineering. With a strong commitment to employee growth, you will have access to cutting-edge resources and opportunities to lead transformative AI and Knowledge Graph solutions for high-profile clients in vibrant cities like London, Berlin, Madrid, and Paris. Join us to be at the forefront of technology while enjoying a supportive environment that values diversity and encourages thought leadership.
StudySmarter Expert Advice🤫
We think this is how you could land Knowledge Engineering Senior Manager/Associate Director
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like WeAreTechWomen!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Knowledge Engineering Senior Manager/Associate Director at WeAreTechWomen.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like WeAreTechWomen.
✨Apply Directly through Our Website
When you find a suitable opening like Knowledge Engineering Senior Manager/Associate Director at WeAreTechWomen, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Knowledge Engineering Senior Manager/Associate Director
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at WeAreTechWomen, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at WeAreTechWomen. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at WeAreTechWomen
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at WeAreTechWomen!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
