Senior Data Analyst

Responsibilities

· Be a bridge between business and digital organizations and part of a cross-disciplinary team, working closely with other 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.

· Maintain metrics and build dashboards.

· Autonomously execute data analysis. You apply existing data & analytics strategies relevant to your immediate scope

· You partner with data engineers to define and build simple data models. You integrate existing tools to automate data ingestion, data manipulation, quality control and data analysis.

· Adhere to and advocate for data analytics best practices.

· Present results to peers and team members

· Collaborates with stakeholders

· Mentor others

- Working knowledge of data science to aid data analysis

- Knowledge of LLMs and putting them into practice for data analysis

Qualifications

· MSc in a quantitative field, preferably statistics.

· Hands-on experience (typically approx 5-7 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.

· Deep understanding of a few and a high-level understanding of several commonly available statistics approaches

· Advanced SQL knowledge

· Advanced scripting experience in R or python.

· Ability to write and maintain moderately complex data pipelines

· 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.

Desired

· Advanced analytics degree

· Experience with big data technologies (e.g. Hadoop, Hive, and Spark) is a plus.

· No prior experience in the energy industry required.