At a Glance
- Tasks: Collect and analyse data on global power projects, focusing on renewables.
- Company: Join Wood Mackenzie, a leader in the power and renewables sector.
- Benefits: Enjoy a supportive work culture with opportunities for growth and development.
- Other info: Collaborate with a diverse team across multiple time zones in an inclusive environment.
- Why this job: Make a real impact in the renewable energy industry while honing your analytical skills.
- Qualifications: Strong analytical skills and a passion for data management in the energy sector.
The predicted salary is between 30000 - 40000 £ per year.
We are looking for a Data Associate to join Wood Mackenzie’s Power and Renewables Project Tracking Data team. The role will focus on data collection via research and supports coverage of the global power industry. Ideal candidates are thoughtful, intellectually curious, and creative, with attention to detail and a dedication to continuous process improvement.
Responsibilities
- Create, monitor, and maintain data relating to power plants by conducting primary and secondary research. Examples of targeted data include renewable project lists, data centers, company financials, asset transactions, tender announcements, and policy developments.
- Evaluate the alignment of our data published sources such as regulatory agencies, market operators, and developer disclosures.
- Collaborate with colleagues across multiple time zones and disciplines to leverage best practices and deliver according to project timelines.
- Perform established workflows to execute data collection and improve data quality.
About You
- Proven analytical capabilities, both qualitative and quantitative.
- Demonstrated interest in data management and in the renewable/energy industry.
- Excellent problem‑solving, documentation, communication and organization skills, with meticulous attention to detail.
- An engaging nature, capable of connecting with co‑workers, clients and industry stakeholders in a wide range of professional settings, including giving presentations.
- A deep intellectual curiosity about what drives markets based on economic principles.
- Passionate ownership of projects and excitement to share accomplishments with fellow Wood Mackenzie employees.
- Strong listening and critical thinking skills.
- Fluency in English; additional language skills are a plus.
- Comfortable working with common Excel functions and query languages.
- Committed to contributing to a welcoming and inclusive environment, sensitive to diverse perspectives, and passionate about equity in the workplace.
Equal Opportunities
We are an equal‑opportunities employer. We are committed to recruiting the best people regardless of their race, colour, religion, age, sex, national origin, disability or protected veteran status.
Data Associate - Power & Renewables employer: Wood Mackenzie
Wood Mackenzie is an exceptional employer for those passionate about the power and renewables sector, offering a collaborative work culture that values intellectual curiosity and continuous improvement. Employees benefit from diverse growth opportunities, engaging in meaningful projects that contribute to global energy solutions while working alongside talented colleagues across various disciplines. Located in a dynamic environment, the company fosters inclusivity and equity, ensuring that every voice is heard and valued.
StudySmarter Expert Advice🤫
We think this is how you could land Data Associate - Power & Renewables
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We think you need these skills to ace Data Associate - Power & Renewables
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
