Material Data Analyst β€” Flexible, Scotland in Glasgow

Material Data Analyst β€” Flexible, Scotland in Glasgow

Glasgow Full-Time 30000 - 40000 Β£ / year (est.) Home office (partial)
SSE

At a Glance

  • Tasks: Support the delivery of a safe network by maintaining accurate material data.
  • Company: SSE, a leader in energy with a commitment to safety and reliability.
  • Benefits: Flexible working options, inclusive workplace, and a range of benefits.
  • Other info: Flexible location within Scotland with opportunities for growth.
  • Why this job: Join a dynamic team and make a real impact on network safety.
  • Qualifications: Strong attention to detail, analytical skills, and ERP system proficiency.

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

SSE is looking for a Material Analyst to support the delivery of a safe and reliable network.

Your base location can be flexible within Scotland, and you'll collaborate closely with various teams to maintain accurate material data.

The role requires strong attention to detail, analytical skills, and proficiency in ERP systems like Maximo and Power BI.

SSE offers a range of flexible benefits and promote an inclusive workplace for all. #J-18808-Ljbffr

SSE

Contact Details:

SSE Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Material Data Analyst β€” Flexible, Scotland in Glasgow

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like SSE!

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✨Apply Directly through Our Website

When you find a suitable opening like Material Data Analyst β€” Flexible, Scotland at SSE, 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 Material Data Analyst β€” Flexible, Scotland in Glasgow

Attention to Detail
Analytical Skills
Proficiency in ERP Systems
Maximo
Power BI
Collaboration Skills
Data 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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at SSE, 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 SSE. 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 SSE

✨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

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at SSE!

✨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.