Senior Data Analyst

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Grade H Responsible for supporting the delivery of business analysis and consulting processes and procedures for the defined specialism using sound technical capabilities, building and maintaining effective working relationships, ensuring relevant standards are defined and maintained, and supporting delivery of process and system improvements. Specialisms: Business Analysis; Data Management and Data Science; Digital Innovation.

Responsibilities

• Part of a cross-disciplinary 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 8+ 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
• 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.
• 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.
• Prior experience in the energy industry desirable.

Responsibilities

• Part of a cross-disciplinary 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 8+ 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
• 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.
• 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.
• Prior experience in the energy industry desirab