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- Tasks: Design and deploy advanced AI/ML solutions for real-time energy intelligence.
- Company: Leading technology firm revolutionising the energy sector.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a team making a real impact in energy innovation with cutting-edge technology.
- Qualifications: PhD in a quantitative field and proficiency in Python required.
- Other info: Collaborative environment with a focus on deploying production-grade systems.
The predicted salary is between 48000 - 72000 £ per year.
A leading technology firm in energy is seeking a Principal Data Scientist to design, implement, and deploy advanced AI/ML methodologies. The ideal candidate will have a PhD in a quantitative field and be fluent in Python, with experience across the full ML lifecycle. Collaboration with various stakeholders is key to develop trading-ready intelligence. The role supports innovative solutions in the energy sector, with a focus on deploying production-grade systems.
Senior Data Scientist — Real-Time Energy Intelligence employer: Vortexa
Contact Detail:
Vortexa Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist — Real-Time Energy Intelligence
✨Tip Number 1
Network like a pro! Reach out to professionals in the energy and data science sectors on LinkedIn. Join relevant groups and participate in discussions to get your name out there and show off your expertise.
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those involving AI/ML methodologies. This will give potential employers a taste of what you can do and how you can contribute to their team.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with the full ML lifecycle and how you've collaborated with stakeholders in past roles.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find and apply for roles that match your skills. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Senior Data Scientist — Real-Time Energy Intelligence
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with AI/ML methodologies and Python in your application. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the Senior Data Scientist position. We love seeing candidates who take the time to connect their experience with what we’re looking for.
Collaboration is Key: Since this role involves working with various stakeholders, mention any relevant teamwork experiences. We appreciate candidates who can demonstrate their ability to collaborate effectively.
Apply Through Our Website: For the best chance of success, make sure you apply through our website. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Vortexa
✨Know Your AI/ML Inside Out
Make sure you brush up on the latest AI and ML methodologies relevant to the energy sector. Be prepared to discuss your experience with the full ML lifecycle, as well as any specific projects where you've implemented these techniques.
✨Showcase Your Python Skills
Since fluency in Python is a must, be ready to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice common data science challenges and be familiar with libraries like Pandas, NumPy, and Scikit-learn.
✨Collaboration is Key
This role involves working with various stakeholders, so highlight your teamwork experiences. Prepare examples of how you've successfully collaborated on projects, especially those that required input from different departments or expertise.
✨Focus on Real-World Applications
Be ready to discuss how your work can lead to innovative solutions in the energy sector. Think about how you've deployed production-grade systems in the past and be prepared to share insights on the impact of your work.
