Data Science Engagement Lead

Location: SHELL CENTRE – CHENNAI
Department: Data Science

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.

Responsibilities

• 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.
• 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.
• Champion change and capability adoption, organizing enablement sessions, roadshows, and awareness programs to promote process-mining and analytics capabilities across business Region/functions.
• Support collaboration with academic and technology partners to explore new analytical methods and contribute insights to product enhancement discussions.
• Mentor and coach data scientists, developing consulting, technical, and storytelling capabilities within the DPT community.
• Monitor industry trends and emerging technologies to provide input on potential future use cases in process analytics, optimization, and AI.

Requirements

• 10–12 years of total experience, including 6+ years in analytics consulting, of which 3+ years in process-mining consulting or process-analytics leadership.
• Bachelor's or Master's degree in Mathematics, Statistics, Economics, Data Science, Engineering, Technical Finance, or a related quantitative field.
• Combines deep analytical expertise with consulting leadership, leveraging prior hands-on experience in analytical solution development and data-driven problem solving.
• Process-Mining Technical Expertise: Strong command of process-mining concepts, algorithms, and tools.
• Led the development and delivery of AI/ML use cases using process-centric data.
• Designed and implemented process data models and event-data integration frameworks.
• Delivered process-analytics and AI-driven consulting engagements across business domains.
• Champions disciplined and responsible data-science delivery.
• Demonstrated strength in analytical storytelling.
• Experience in leading and active engagement in professional communities.
• Proven expertise in applying process mining, optimization, machine learning, or AI techniques.
• Strong proficiency in Python, SQL, and process data modeling.
• Deep understanding of process data structures.
• Structured, hypothesis-driven problem-solving approach.
• Ability to guide cross-functional teams.
• Experience with cloud-based analytics environments and process-analytics platforms.
• Understanding of end-to-end business-process lifecycles.
• Knowledge of process simulation, optimization, or Operations Research (OR) techniques.
• Strong data storytelling and visualization skills.
• Continuous-learning mindset.
• Experience with complementary or open-source process-mining tools.
• Research and innovation orientation.

Benefits

• Progress as a person while working on the energy transition.
• Continuously grow transferable skills.
• Work at the forefront of technology, trends, and practices.
• Collaborate with experienced colleagues.
• Achieve balance in a values-led culture.
• Join an organization working to become one of the most diverse and inclusive in the world.
• Grow through diverse career opportunities.
• Gain access to a wide range of training and development programs.