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- Tasks: Develop data models and automate pipelines to optimise energy solutions.
- Company: Leading energy company focused on digital innovation.
- Benefits: Competitive salary, full-time role, and opportunities for professional growth.
- Why this job: Join a pioneering team and make a significant impact in energy optimisation.
- Qualifications: 10+ years in data analytics with strong Python and SQL skills.
- Other info: Collaborative environment with a focus on communication and teamwork.
The predicted salary is between 54000 - 84000 £ per year.
A leading energy company is seeking a Data Scientist to enhance its digital optimization solutions. The role involves developing data models, automating data pipelines, and leveraging machine learning techniques to improve forecasting and decision-making.
Candidates should have at least 10 years of experience in data analytics and strong skills in Python and SQL. Excellent collaboration and communication skills are essential.
The position is full-time and based in Saudi Arabia, with specific details to be included in the job offer.
Lead Data Scientist, Global Energy Optimization employer: Aramco
Contact Detail:
Aramco Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist, Global Energy Optimization
✨Tip Number 1
Network like a pro! Reach out to professionals in the energy sector on LinkedIn or at industry events. We can leverage our connections to get insights and maybe even a referral for that Lead Data Scientist role.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data models and projects, especially those involving machine learning and automation. We want to demonstrate how we can enhance digital optimisation solutions.
✨Tip Number 3
Practice makes perfect! Get ready for interviews by rehearsing common questions related to data analytics, Python, and SQL. We should also be prepared to discuss our collaboration and communication skills, as they’re key for this role.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. We’ve got all the resources you need to make your application stand out for that full-time position in Saudi Arabia.
We think you need these skills to ace Lead Data Scientist, Global Energy Optimization
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your 10+ years in data analytics. We want to see how your experience aligns with the role, especially in developing data models and automating pipelines. Use specific examples to showcase your skills in Python and SQL!
Tailor Your Application: Don’t just send a generic CV! We love it when candidates tailor their applications to fit the job description. Mention how your past projects relate to enhancing digital optimisation solutions in the energy sector.
Communicate Clearly: Since excellent collaboration and communication skills are essential, make sure your application reflects this. Write clearly and concisely, and don’t hesitate to show your personality – we’re looking for someone who can engage with the team!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates about the position. Let’s get started!
How to prepare for a job interview at Aramco
✨Know Your Data Inside Out
Make sure you’re well-versed in the latest data analytics techniques and tools, especially Python and SQL. Brush up on your experience with data models and automation, as you’ll want to showcase how you can enhance digital optimisation solutions.
✨Showcase Your Machine Learning Skills
Prepare to discuss specific machine learning techniques you’ve used in past projects. Be ready to explain how these methods improved forecasting and decision-making in your previous roles, as this will demonstrate your practical knowledge and problem-solving abilities.
✨Collaboration is Key
Since excellent collaboration skills are essential for this role, think of examples where you successfully worked in a team. Highlight how you communicated complex data insights to non-technical stakeholders, as this will show your ability to bridge the gap between data science and business needs.
✨Research the Company and Its Goals
Familiarise yourself with the company’s mission and recent projects in energy optimisation. This will not only help you tailor your answers but also show your genuine interest in contributing to their goals, making you a more appealing candidate.
