At a Glance
- Tasks: Lead AI deployment projects and shape innovative Celonis solutions.
- Company: Join Celonis, a leader in data-driven orchestration and AI solutions.
- Benefits: Enjoy hybrid work options, competitive salary, and career growth opportunities.
- Other info: Collaborative environment with a focus on high-impact engagements.
- Why this job: Make a real impact by guiding strategic accounts with cutting-edge AI technology.
- Qualifications: Expertise in Celonis, data integration, and AI orchestration required.
The predicted salary is between 80000 - 100000 £ per year.
Celonis is seeking a Lead Deployment Architect for AI in London- or UK-based operations.
This senior role sits within Celonis Services, guiding strategic accounts and shaping architecture and delivery of Celonis solutions to achieve measurable outcomes.
The position requires deep expertise in Celonis, data integration, and AI-driven orchestration, with hybrid work options.
You will lead high-impact engagements, collaborate with product teams, and define best-practice AI-augmented delivery
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Senior AI Deployment Architect — Orchestration Lead employer: Celonis
Celonis is an exceptional employer that fosters a dynamic work culture centred around innovation and collaboration. With a strong emphasis on employee growth, we offer extensive training opportunities and the chance to work with cutting-edge technologies in a vibrant location. Join us to be part of a team that values your contributions and supports your professional journey in delivering impactful solutions for our customers.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Deployment Architect — Orchestration Lead
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We think you need these skills to ace Senior AI Deployment Architect — Orchestration Lead
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!
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Craft a Tailored Cover Letter:For a full-time role at Celonis, 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 Celonis. 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 Celonis
✨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!
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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 Celonis!
✨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.
