Value Consultant - Data Analytics & Supply Chain Transformation

Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology.
As one of the world's fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what's possible.
We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action.
We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process.
Join our mission to make processes work for people, companies, and the planet.
The Role As a Value Consultant ( Value Engineer ) you are spearheading our mission of data-driven business transformation with our customers and prospects pushing the envelope in solving business-critical problems driven with our AI Process Intelligent Platform.
You will work in partnership with the Celonis Sales Team and have full responsibility for the end-to-end value journey of our customers.
You are our customers' trusted advisor and help them achieve their strategic goals and realize significant value using the Celonis Platform.
In collaboration with our services and tech partners, you will drive measurable business impact across various processes and industries and accelerate the adoption of our platform.
You will blend deep process and industry expertise with a proven consulting skill set with strong AI and analytical skills at the forefront of one of the fastest-growing tech companies worldwide.
What you will do Identify & Frame Value (Win Accounts): Work closely with the Sales team to define the account strategy and pitch corporate prospects.
Translate high-level business needs across key sectors (Manufacturing, Retail, Finance, Supply Chain) into critical AI and process-mining use cases, building the tailored business cases, technical demos, and Proof-of-Value projects needed to win new accounts.
Realize Value (Execute & Deliver Impact): Govern and drive the execution of the business-critical implementation plan defined in the framing stage.
Collaborate directly with delivery teams and the customer's in-house services to ensure solutions (leveraging SaaS, Python, or generative AI) are effectively deployed, tracking and unlocking maximum operational value and ROI for senior leadership.
Scale Value (Grow Accounts): Drive account growth, adoption, and renewals by embedding Celonis as a strategic transformation platform.
Oversee multidisciplinary account teams to manage project scopes and timelines, aligning continuously with Sales to identify expansion roadmaps and effectively communicate results directly to C-level executives.
Ensure CIO and C-level business alignment and sponsorship.
Native-level Spanish proficiency is required.
Candidates must be able to lead customer workshops, conduct executive presentations, and manage stakeholder interactions in Spanish.
The qualifications you need +4 years of experience leading technical pre-sales, delivery projects, including defining AI roadmaps, building compelling ROI/TCO critical business cases and prototyping of machine learning and generative AI solutions as well as ensuring health and expansion within the customer journey.
Domain/Industry Expertise: experience of the supply chain domain across sectors (Manufacturing, Consumer, Retail, Services and Resources) with the ability to translate high-level business needs into specific business-critical AI use cases.
AI, Data, Analytics: fundamentals of data science, how to create meaningful use cases for generative AI for business, understanding of generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
Good knowledge of Business Software / SaaS applications (e.g. SAP, Oracle), experience with implementing RPA and/or BI Tools and/or building Dashboards.
Knowledge of one of the following: Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
SQL is a must.
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