Job summary

Grade IResponsible for supporting the delivery of business analysis and consulting processes and procedures for the defined specialism using basic technical capabilities, developing working relationships to provide support with queries, issues and ad-hoc requests and assisting with quality assurance services. Specialisms: Business Analysis; Data Management and Data Science; Digital Innovation.
Responsibilities
Identify, analyze and interpret trends or patterns in complex data sets. Provide support to business teams in requirements gathering and validation. Display strong problem-solving and quantitative skills, including the ability to dis-aggregate issues, identify root causes and recommend solutions. Possess a strong understanding and working knowledge of business intelligence/visualization tools (e.g. PowerApps/Power BI). Demonstrate good communication, team-orientation and people skills

• Part of a cross-disciplinary product team, working closely with other data analysts, product managers, data scientists, data engineers, software engineers, data managers and business partners.
• Provide actionable, data-driven business and product insights by combining deep statistical skills, data manipulation capabilities and business acumen.
• Define, instrument and maintain metrics and build dashboards.
• Proactively identify impactful opportunities and autonomously execute data analysis.
• Be a bridge between business and digital organizations, combining in-depth understanding of both areas.
• If needed, build and maintain data pipelines to unblock your analysis.
• Adhere to and advocate for data analytics best practices
• Present results to peers and senior management, influencing decision making
• Mentor others.

Qualifications

• Hands-on experience (typically 5+ years) carrying out data analytics, data mining and product analytics in complex, fast-paced environments.
• Applied knowledge of data analytics and data pipelining tools and approaches across all data lifecycle stages.
• Thorough understanding of underlying mathematical foundations of statistics, including knowledge of experimental design and analysis and causal inference from observational data.
• Expert SQL knowledge, Expert in data Visualisation techniques and best practices
• Advanced scripting experience in R or python.
• Ability to write and maintain moderately complex data pipelines
• Experience with big data technologies (e.g. Hadoop, Hive, and Spark) is a plus.
• Advanced level knowledge on PowerBI/PowerApp/PowerPlatform is a plus
• Strong business acumen.
• Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.
• Strong communication and stakeholder management skills. Ability to lead large organizations through influence.
• Continuous learning and improvement mindset.
• MSc in a quantitative field, preferably statistics.
• No prior experience in the energy industry required.

Responsibilities
Identify, analyze and interpret trends or patterns in complex data sets. Provide support to business teams in requirements gathering and validation. Display strong problem-solving and quantitative skills, including the ability to dis-aggregate issues, identify root causes and recommend solutions. Possess a strong understanding and working knowledge of business intelligence/visualization tools (e.g. PowerApps/Power BI). Demonstrate good communication, team-orientation and people skills

• Part of a cross-disciplinary product team, working closely with other data analysts, product managers, data scientists, data engineers, software engineers, data managers and business partners.
• Provide actionable, data-driven business and product insights by combining deep statistical skills, data manipulation capabilities and business acumen.
• Define, instrument and maintain metrics and build dashboards.
• Proactively identify impactful opportunities and autonomously execute data analysis.
• Be a bridge between business and digital organizations, combining in-depth understanding of both areas.
• If needed, build and maintain data pipelines to unblock your analysis.
• Adhere to and advocate for data analytics best practices
• Present results to peers and senior management, influencing decision making
• Mentor others.

Qualifications

• Hands-on experience (typically 5+ years) carrying out data analytics, data mining and product analytics in complex, fast-paced environments.
• Applied knowledge of data analytics and data pipelining tools and approaches across all data lifecycle stages.
• Thorough understanding of underlying mathematical foundations of statistics, including knowledge of experimental design and analysis and causal inference from observational data.
• Expert SQL knowledge, Expert in data Visualisation techniques and best practices
• Advanced scripting experience in R or python.
• Ability to write and maintain moderately complex data pipelines
• Experience with big data technologies (e.g. Hadoop, Hive, and Spark) is a plus.
• Advanced level knowledge on PowerBI/PowerApp/PowerPlatform is a plus
• Strong business acumen.
• Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.
• Strong communication and stakeholder management skills. Ability to lead large organizations through influence.
• Continuous learning and improvement mindset.
• MSc in a quantitative field, preferably statistics.
• No prior experience in the energy industry required.

Responsibilities
Identify, analyze and interpret trends or patterns in complex data sets. Provide support to business teams in requirements gathering and validation. Display strong problem-solving and quantitative skills, including the ability to dis-aggregate issues, identify root causes and recommend solutions. Possess a strong understanding and working knowledge of business intelligence/visualization tools (e.g. PowerApps/Power BI). Demonstrate good communication, team-orientation and people skills

• Part of a cross-disciplinary product team, working closely with other data analysts, product managers, data scientists, data engineers, software engineers, data managers and business partners.
• Provide actionable, data-driven business and product insights by combining deep statistical skills, data manipulation capabilities and business acumen.
• Define, instrument and maintain metrics and build dashboards.
• Proactively identify impactful opportunities and autonomously execute data analysis.
• Be a bridge between business and digital organizations, combining in-depth understanding of both areas.
• If needed, build and maintain data pipelines to unblock your analysis.
• Adhere to and advocate for data analytics best practices
• Present results to peers and senior management, influencing decision making
• Mentor others.

Qualifications

• Hands-on experience (typically 5+ years) carrying out data analytics, data mining and product analytics in complex, fast-paced environments.
• Applied knowledge of data analytics and data pipelining tools and approaches across all data lifecycle stages.
• Thorough understanding of underlying mathematical foundations of statistics, including knowledge of experimental design and analysis and causal inference from observational data.
• Expert SQL knowledge, Expert in data Visualisation techniques and best practices
• Advanced scripting experience in R or python.
• Ability to write and maintain moderately complex data pipelines
• Experience with big data technologies (e.g. Hadoop, Hive, and Spark) is a plus.
• Advanced level knowledge on PowerBI/PowerApp/PowerPlatform is a plus
• Strong business acumen.
• Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.
• Strong communication and stakeholder management skills. Ability to lead large organizations through influence.
• Continuous learning and improvement mindset.
• MSc in a quantitative field, preferably statistics.
• No prior experience in the energy industry required.