- As a Data Science Analyst within the Digital Process Twin (DPT) portfolio, you will apply data science methods to process event data to support analytical modeling, process insights, and data-driven decision-making. Working alongside experienced data scientists, engineers, and process analysts, you will help prepare, analyze, and visualize data to reveal opportunities for improving business process efficiency and performance.
- 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 exploring process event data, developing analytical insights, and learning how data science enhances operational agility, we invite you to join us as a Data Science Analyst contributing to Shell s digital process transformation journey.
Whats the role
- Support the preparation, cleansing, and transformation of process event data for analysis and modeling.
- Assist in exploratory data analysis (EDA) to identify trends, patterns, and anomalies in process data.
- Contribute to data visualization, dashboards, and reports to communicate insights using tools such as Power BI, Tableau, or Plotly Dash.
- Collaborate with data scientists to design and test features and metrics for process performance and prediction models, gaining exposure to analytical design principles and learning from implementation feedback.
- Participate in the creation and maintenance of process data models and pipelines, ensuring data quality and consistency.
- Work with cross-functional teams to integrate data from multiple enterprise systems (e.g., SAP, Salesforce, ServiceNow) for process analysis.
- Support process mining initiatives by preparing event logs and assisting with analyses on platforms like Celonis EMS or SAP Signavio.
- Contribute to documentation, testing, and quality assurance for analytical deliverables.
- Develop foundational understanding of Responsible AI and Explainable AI (XAI) concepts.
What you bring
- 0-2 years of experience in data analytics or data science, including exposure to data preparation, analysis, or visualization.
- Basic understanding of machine learning or statistical techniques applied to structured or event data.
- Experience with Python, SQL, and data manipulation libraries (e.g., pandas, NumPy).
- Exposure to data visualization tools and frameworks such as Power BI, Tableau, Plotly Dash, or Matplotlib/Seaborn.
- Familiarity with process event or behavioral data and understanding of event logs (case IDs, activities, timestamps) is desirable.
- Exposure to process-mining platforms (e.g., Celonis EMS, SAP Signavio, or PM4Py) is an advantage.
- Knowledge of data quality, ETL concepts, or pipeline design is preferred.
- Enthusiasm to learn AI/ML, process analytics, and MLOps practices in enterprise environments.
- Bachelor s or Master s degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field.
- Proficiency in Python and SQL for data analysis and transformation.
- Basic knowledge of machine learning or predictive modeling concepts.
- Strong analytical and problem-solving mindset with attention to detail.
- Ability to learn and apply process-oriented data science methods.
- Exposure to process mining and understanding of event-based data.
- Experience using data visualization tools and frameworks such as Power BI, Tableau, or Plotly Dash for process-performance reporting
- Understanding of data quality, data wrangling, and feature engineering.
- Exposure to Celonis EMS, SAP Signavio, or open-source process-mining frameworks (PM4Py, ProM).
- Academic or project experience in process simulations or operations research.
- Awareness of professional data science communities and willingness to engage for learning and growth.
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.
