About this role
Data Science Engagement Lead
What’s the role
The Commercial Data Science (CDS) team is a community of experts partnering with Shell’s business stakeholders to deliver data-driven solutions through deep process understanding and technical excellence.
As a Data Science Engagement Lead within the Digital Process Twin (DPT) portfolio, you will lead data scientists and collaborate with cross-functional business teams to identify transformation opportunities using process-centric data and guide the application of process mining, optimization, and AI/ML techniques to improve operational performance. Your work will drive measurable business outcomes by enhancing visibility, agility, and efficiency across Shell’s business operations.
The DPT Centre of Excellence (CoE) aims to “Empower Process Transformation through Digital Process Twins” by applying advanced process mining and analytics capabilities. Shell is recognized as an industry leader in process mining, pioneering innovative analytical approaches and advancing the process twin concept. The CoE actively engages with academic partners, industry forums, and technology vendors to drive research, innovation, and thought leadership.
If you are passionate about applying data science to process event data to drive organizational process transformation and value collaboration, innovation, and continuous learning we invite you to join us as a Data Science Engagement Lead.
What you’ll be doing
- Lead process-mining consulting engagements, translating business challenges into analytical problem statements and actionable insights that drive measurable digital process transformation.
- Partner with global and regional business stakeholders to uncover inefficiencies, define transformation opportunities, and generate process-analytics use cases aligned with the Integrated Process Plan (IPP).
- Oversee the design and development of process data models, collaborating with process and data architects to ensure clean, integrated, and analysis-ready event data from enterprise systems (e.g., SAP, Salesforce, ServiceNow).
- Facilitate process discovery and value workshops, translating analytical findings into tangible business outcomes through clear, evidence-based, and persuasive data storytelling.
- Guide the delivery of analytical and AI/ML solutions, ensuring alignment with strategic priorities, technical excellence, and measurable value realization (e.g., process cycle-time reduction or cost-efficiency improvement).
- Champion change and capability adoption, organizing enablement sessions, roadshows, and awareness programs to pro