Data Science Engagement Lead

Role Overview Shell's Commercial Data Science team is seeking a seasoned Data Science Engagement Lead to spearhead the Digital Process Twin Centre of Excellence. In this role, you will lead a team of data scientists and collaborate with cross-functional business stakeholders to deliver process-centric analytics, AI/ML solutions, and process mining capabilities that drive measurable operational improvements across Shell's global business functions. This is a strategic leadership position that blends deep analytical expertise with consulting acumen to enable true digital process transformation. Key Responsibilities - Lead end-to-end process mining consulting engagements, converting business challenges into structured analytical problem statements and actionable transformation insights - Partner with global business stakeholders to identify process inefficiencies and define data-driven transformation opportunities aligned with the Integrated Process Plan - Oversee design and development of process data models, working with data and process architects to ensure clean, integration-ready event data from enterprise platforms such as SAP, Salesforce, and ServiceNow - Facilitate value workshops and process discovery sessions, communicating analytical findings through compelling, evidence-based data storytelling to executive and business audiences - Guide delivery of AI and ML solutions ensuring alignment with strategic priorities, technical standards, and value realization targets such as cycle-time reduction and cost efficiency - Champion capability adoption by organizing enablement sessions, roadshows, and awareness initiatives to promote analytics across business regions and functions - Mentor and coach data scientists within the DPT community on technical, consulting, and storytelling competencies - Collaborate with academic and technology partners to explore new analytical methods and contribute to Shell's Digital Process Twin product evolution - Monitor emerging technologies and industry trends to identify future opportunities in process analytics, optimization, and AI Required Qualifications - 10 to 12 years of total professional experience with at least 6 years in analytics consulting, including 3 or more years focused on process mining or process analytics leadership in global organizations - Bachelor's or Master's degree in Mathematics, Statistics, Economics, Data Science, Engineering, Finance, or a related quantitative discipline - Strong command of process mining concepts, algorithms, and platforms such as Celonis EMS, SAP Signavio, and PM4Py - Proven experience delivering AI and ML use cases using process-centric data integrating predictive and prescriptive models with process mining insights - Proficiency in Python, SQL, and process data modeling with hands-on experience processing data from enterprise systems including SAP, Salesforce, HANA, and ServiceNow - Experience with cloud-based analytics environments including Azure, AWS, or GCP and familiarity with MLOps and DevOps workflows - Strong data storytelling and visualization skills with the ability to communicate complex analytics to diverse audiences - Knowledge of Agile practices, Responsible AI principles, and structured hypothesis-driven problem-solving approaches - Understanding of end-to-end business process lifecycles, value chain optimization, and Operations Research techniques Why Join Us At Shell, you will work alongside talented professionals tackling one of the world's most critical energy challenges, with access to diverse career paths, world-class training programs, and a deeply inclusive culture that values honesty, integrity, and continuous learning. Shell India's three capability centres in Bangalore and Chennai serve as a global hub for digital innovation, offering you the opportunity to work at the cutting edge of technology and energy transformation.

- 10-12 years of experience with 6+ years in analytics consulting and 3+ years in process mining leadership - Bachelor's or Master's degree in a quantitative field such as Data Science, Engineering, or Mathematics - Expertise in process mining tools including Celonis EMS, SAP Signavio, and PM4Py - Strong proficiency in Python, SQL, and process data modeling - Experience delivering AI and ML solutions using process-centric data - Hands-on knowledge of enterprise systems such as SAP, Salesforce, HANA, and ServiceNow - Experience with cloud platforms including Azure, AWS, or GCP - Familiarity with MLOps, DevOps workflows, GitHub, and CI/CD pipelines - Strong analytical storytelling and executive communication skills - Knowledge of Agile delivery practices and Responsible AI principles - Understanding of business process lifecycles, procurement, finance, and supply chain domains - Experience with process simulation, optimization, or Operations Research techniques - Continuous learning mindset with awareness of emerging AI and digital twin technologies

- Opportunity to work on global energy transition challenges - Access to diverse national and international career opportunities - Comprehensive training and development programmes - Inclusive and progressive workplace culture - Collaboration with academic and technology innovation partners - Work at the forefront of digital innovation and cutting-edge technology - Supportive environment for employees of all backgrounds and abilities