At a Glance
- Tasks: Support commercial activities with market intelligence and forecasting in the subsea energy sector.
- Company: Join Boskalis Subsea Services, a leader in innovative energy solutions.
- Benefits: Competitive salary, career development opportunities, and a dynamic work environment.
- Other info: Collaborate with Business Development and Tendering teams for strategic planning.
- Why this job: Make a real impact in the subsea energy industry with your analytical skills.
- Qualifications: 7+ years as a Market Analyst in Subsea/Oil & Gas, strong Excel and CRM skills.
The predicted salary is between 60000 - 84000 £ per year.
Boskalis Subsea Services in Aberdeen seeks a Market Analyst to support commercial activities through market intelligence, forecasting, and insights.
You will work with Business Development and Tendering teams, maintain market data, and develop forecasting models for strategic planning.
Requirements include 7+ years in a Market Analyst role within the Subsea/Oil & Gas sector, strong Excel and CRM skills, and excellent data presentation abilities.
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Strategic Market Analyst - Subsea Energy Insights employer: Boskalis
Boskalis is an excellent employer, offering a dynamic work environment in Aberdeen where innovation and teamwork thrive. With competitive compensation, a contributory pension scheme, and robust opportunities for career development, employees are encouraged to grow their skills and advance within the company. The supportive culture and commitment to safety ensure that every team member can contribute meaningfully to exciting subsea operations.
StudySmarter Expert Advice🤫
We think this is how you could land Strategic Market Analyst - Subsea Energy Insights
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We think you need these skills to ace Strategic Market Analyst - Subsea Energy Insights
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 Boskalis, 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 Boskalis. 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 Boskalis
✨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!
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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 Boskalis!
✨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.
