Remote Data Analysis Lead - Energy & Finance Insight in Glasgow

Remote Data Analysis Lead - Energy & Finance Insight in Glasgow

Glasgow Full-Time 30000 - 40000 £ / year (est.) No working from home possible
Avomind

At a Glance

  • Tasks: Lead data analysis and translate findings into actionable insights for energy and finance.
  • Company: Avomind, a forward-thinking company focused on energy transition.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and career development.
  • Why this job: Make a real impact in the energy sector while developing your analytical skills.
  • Qualifications: 1-2 years of experience in data analysis and a background in finance.

The predicted salary is between 30000 - 40000 £ per year.

Avomind is seeking a data-driven analyst to lead our data team. You will oversee import and analysis from diverse sources and translate findings into actionable insights.

With 1-2 years of experience and a finance background, you will contribute to energy transition coverage, collaborate across departments, and help shape reporting and publications. Hybrid work supports balance and growth.

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Remote Data Analysis Lead - Energy & Finance Insight in Glasgow employer: Avomind

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Avomind

Contact Details:

Avomind Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Remote Data Analysis Lead - Energy & Finance Insight in Glasgow

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Apply Directly through Our Website

When you find a suitable opening like Remote Data Analysis Lead - Energy & Finance Insight at Avomind, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Remote Data Analysis Lead - Energy & Finance Insight in Glasgow

Data Analysis
Analytical Skills
Finance Background
Collaboration Skills
Reporting Skills
Actionable Insights Generation
Project Management

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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Craft a Tailored Cover Letter:For a full-time role at Avomind, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Avomind. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Avomind

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

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.