Description

About Octopus Energy / Shell Energy Octopus Energy is part of Shell’s global energy portfolio, focusing on sustainable, efficient, and data-driven energy solutions. The organization emphasizes innovation, analytics-led decision-making, and inclusive growth while supporting the global energy transition. Job Summary Octopus Energy is seeking a Data Science Analyst to support data-driven process analytics and modeling initiatives. The role focuses on data preparation, exploratory analysis, visualization, and collaboration with data science teams to improve process performance and operational decision-making across enterprise systems. Key Responsibilities Data Preparation & Analysis Prepare, cleanse, and transform process event data for analysis and modeling Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies Support feature creation and metric design for process performance and prediction models Data Visualization & Reporting Develop dashboards and analytical reports using Power BI, Tableau, or Plotly Dash Communicate insights clearly to technical and non-technical stakeholders Process Analytics & Mining Support process mining initiatives by preparing event logs (case IDs, activities, timestamps) Assist with analysis using platforms such as Celonis EMS, SAP Signavio, or PM4Py Contribute to process-performance measurement and optimization studies Data Engineering & Quality Assist in building and maintaining data pipelines and process data models Ensure data quality, consistency, and validation across multiple enterprise systems Support ETL workflows and documentation, testing, and quality assurance Collaboration & Learning Work with cross-functional teams to integrate data from SAP, Salesforce, ServiceNow, and other systems Develop foundational understanding of Responsible AI and Explainable AI (XAI) Continuously learn AI/ML, process analytics, and MLOps practices Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field 0–2 years of experience in Data Analytics or Data Science Strong proficiency in Python and SQL for data analysis and transformation Technical Skills Python (pandas, NumPy, Matplotlib/Seaborn) SQL and relational databases Data visualization tools: Power BI, Tableau, Plotly Dash Basic knowledge of machine learning and statistical techniques Understanding of data wrangling, feature engineering, and data quality concepts Exposure to process mining tools (Celonis, SAP Signavio, PM4Py) is a plus Key Competencies Strong analytical and problem-solving skills Attention to detail and data accuracy Ability to work with event-based and behavioral data Willingness to learn process-oriented data science methods Good communication and collaboration skills What We Offer Opportunity to work on energy transition and sustainability initiatives Exposure to cutting-edge data science and process analytics technologies Collaborative, inclusive, and values-driven work culture Continuous learning and career development opportunities Work with experienced professionals across global teams

Role and Responsibilities

• Key Responsibilities Data Preparation & Analysis Prepare, cleanse, and transform process event data for analysis and modeling Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies Support feature creation and metric design for process performance and prediction models Data Visualization & Reporting Develop dashboards and analytical reports using Power BI, Tableau, or Plotly Dash Communicate insights clearly to technical and non-technical stakeholders Process Analytics & Mining Support process mining initiatives by preparing event logs (case IDs, activities, timestamps) Assist with analysis using platforms such as Celonis EMS, SAP Signavio, or PM4Py Contribute to process-performance measurement and optimization studies Data Engineering & Quality Assist in building and maintaining data pipelines and process data models Ensure data quality, consistency, and validation across multiple enterprise systems Support ETL workflows and documentation, testing, and quality assurance Collaboration & Learning Work with cross-functional teams to integrate data from SAP, Salesforce, ServiceNow, and other systems Develop foundational understanding of Responsible AI and Explainable AI (XAI) Continuously learn AI/ML, process analytics, and MLOps practices