Job Description

, India
Job Family Group: Research and Development
Worker Type: Regular
Posting Start Date: January 20, 2026
Business Unit: Finance
Experience Level: Early Careers
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What's the role
The Commercial Data Science (CDS) team partners with Shell's business units to deliver data-driven solutions through deep process understanding and technical excellence.
As an Associate Data Scientist within the Digital Process Twin (DPT) portfolio, you will apply data science techniques on process event data to uncover patterns, identify inefficiencies, and support end-to-end business process optimization. You will collaborate with senior data scientists, engineers, and process experts to develop analytical models, transform data into insights, and contribute to Shell's process-mining ecosystem.
The Digital Process Twin Centre of Excellence (CoE) aims to "Empower Process Transformation through Digital Process Twins" by advancing process-mining and analytics capabilities. Shell is recognized as an industry thought leader in process intelligence, pioneering innovative analytical methodologies and data-driven process transformation. The CoE collaborates with academic institutions, industry forums, and technology vendors to drive innovation and applied research in process analytics.
If you are passionate about building analytical models using process event data and developing intelligent solutions that enhance operational agility and enable autonomous processes, we invite you to join us as an Associate Data Scientist contributing to Shell's digital process transformation journey.
What you will be doing

• Assist in the development, and testing of machine learning, statistical, and optimization models using process event data.
• Apply data science and AI/ML techniques to analyze process flows, detect patterns, and identify improvement opportunities.
• Participate in process data model design and preparation, integrating and transforming data from enterprise systems such as SAP, Salesforce, and ServiceNow into analysis-ready structures under technical supervision
• Support data pipeline development and validation for process analytics and model deployment.
• Collaborate with senior data scientists and engineers to deploy analytical models into the process-mining platform (e.g., Celonis EMS, SAP Signavio, or PM4Py).
• Build and enhance data visualizations, dashboards, and analytical reports that communicate process insights and model outcomes using visualization tools and frameworks (e.g., Power BI, Tableau, Plotly Dash, Matplotlib, Seaborn).
• Support MLOps and DevOps workflows, including version control, model testing, and continuous integration using GitHub and CI/CD pipelines.
• Contribute to small analytical components or prototype builds, co-owning parts of model or feature engineering tasks with clear design direction.
• Follow Responsible AI and Explainable AI (XAI) principles during model development and analysis activities.

What you bring

• 2-4 years of experience in data science, including hands-on development of AI/ML or optimization models, and at least 1 year working with process event or behavioral data.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field.
• Exposure to applying machine learning, statistical modeling, or process-mining techniques to enterprise or large-scale datasets.
• Proficiency in Python, SQL, and data-modeling techniques for event or process data.
• Experience supporting or developing process data models and analytical pipelines, integrating data from enterprise systems such as SAP, Salesforce, or ServiceNow.
• Familiarity with process-mining platforms (e.g., Celonis EMS, SAP Signavio, PM4Py, or ProM).
• Understanding of Agile, MLOps, and DevOps workflows for version control, testing, and model deployment.
• Basic understanding of process data structures (case IDs, activities, timestamps, attributes) and their use in process-performance analysis.
• Exposure to cloud-based environments (Azure, AWS, or GCP) for data science workloads is desirable.
• Demonstrates growing independence by delivering assigned components within defined frameworks and under technical supervision.

Must have Skills:

• Proficiency in Python, SQL, and data-modeling techniques for event/process data.
• Exposure to process event data, event-log structures, and process-performance analysis.
• Hands-on experience in data preparation and feature engineering for analytical models.
• Foundational understanding of machine learning and statistical modeling techniques.
• Strong analytical thinking and curiosity to explore data-driven process improvements.

Should have Skills:

• Experience with data visualization tootls and frameworks (Power BI, Plotly Dash, etc..) for analytical storytelling and process-performance reporting.
• Knowledge of Celonis EMS, SAP Signavio, or open-source process-mining tools (PM4Py, ProM).
• Familiarity with process data model design and deployment.
• Understanding of MLOps concepts (CI/CD, GitHub, Docker, MLflow).
• Awareness of Responsible AI and model interpretability frameworks.

Nice have Skills:

• Exposure to big data frameworks (Spark, Databricks).
• Interest in participating in professional communities, forums, or hackathons to learn and collaborate in data science and analytics.
• Familiarity with cloud ML environments (Azure ML, AWS SageMaker, GCP Vertex AI).

What we offer
You bring your skills and experience to Shell and in return you work with talented, committed people on one of the most important challenges facing our planet. You'll have the opportunity to develop the skills you need to grow in an environment where we value honesty, integrity, and respect for one another. You'll be able to balance your priorities as you become the best version of yourself.

• Progress as a person as we work on the energy transition together.
• Continuously grow the transferable skills you need to get ahead.
• Work at the forefront of technology, trends, and practices.
• Collaborate with experienced colleagues with unique expertise.
• Achieve your balance in a values-led culture that encourages you to be the best version of yourself.
• Join an organisation working to become one of the most diverse and inclusive in the world. We strongly encourage applicants of all genders, ages, ethnicities, cultures, abilities, sexual orientation, and life experiences to apply.
• Grow as you progress through diverse career opportunities in national and
• international teams.
• Gain access to a wide range of training and development programmes.

An Inclusive & Progressive Place to Work

• To power progress together, we need to attract and develop the brightest minds and make sure every voice is heard. Here are just some of the ways we're nurturing an inclusive environment - one where you can express your ideas, extend your skills, and reach your potential.
• We're creating a space where people with disabilities can excel through transparent recruitment process, workplace adjustments and ongoing support in their roles. Feel free to let us know about your circumstances when you apply, and we'll take it from there.
• We're closing the gender gap - whether that's through action on equal pay or by enabling more women to reach senior roles in engineering and technology.
• We're striving to be a pioneer of an inclusive and diverse workplace, promoting equality for employees regardless of sexual orientation or gender identity.

Shell in India
Shell is a diversified energy company in India with 13,000 employees, and presence in Integrated Gas, Downstream, Power, Renewable and Upstream. Additionally, we have deep capabilities in R&D, digitalisation, and business operations.
Our global strategy, Powering Progress, is designed to generate value for our shareholders, customers, and the wider society, and focuses on creating more value with less emissions. The strategy supports our purpose of providing more and cleaner energy solutions, with the aim of profitably transforming Shell into a net-zero emissions energy business by 2050. As India moves towards its target of net-zero emissions by 2070, Shell India aims to play a leading role in securing vital energy for today, while investing in, and helping to build, the energy system of the future through strategic investments in the country.
Our Lubricants business serves over 50,000 consumers through a strong network of over 200 distributors, and operates an end-to-end value chain that spans conceptualization, development, and production at a world-class blending plant at Taloja. Through our 350-plus retail stations, we offer an integrated mobility experience including fuels, cafes, and convenience stores, with a prominent network of EV recharging facilities.
Shell owns and operates a LNG re-gasification terminal at Hazira, Surat, with a capacity of 5 MTPA and a LNG truck-loading unit that plays a crucial role in helping meet India's growing demand for gas across sectors. In 2022, Shell acquired Sprng Energy in a $1.55 billion deal to build an integrated energy transition business in the country. Sprng is a leading renewable energy company in India which develops and manages solar, wind, and hybrid power generation facilities and infrastructure.
Our three capability centres across Bangalore and Chennai serve as a technology and innovation powerhouse for Shell globally, working as a delivery engine for core technical, digital, and finance processes: pioneering digital innovation and cutting-edge technologies across the energy sector. We also have strong academic partnerships and collaborations with leading universities and technology institutes to accelerate decarbonization efforts within the energy sector.
We are committed to positively contributing to the communities in which we operate through programmes on STEM Education, Skilling, and Livelihood across India. We nurture and invest in startups developing initiatives focused on accelerating energy innovation through programs such as Shell E4 and Shell Eco-marathon. We also have strategic investments in new energy companies such as Husk Power, d.light, Orb Energy, and Cleantech Solar.
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Skills Required