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- Tasks: Lead predictive workforce modelling initiatives and analyse large datasets.
- Company: Major energy provider in London with a focus on innovation.
- Benefits: Competitive salary, 7.5% bonus, annual leave, and private medical cover.
- Why this job: Make a real impact in the energy sector while developing your data science skills.
- Qualifications: Strong background in Python, statistical methods, and causal modelling.
- Other info: Collaborate with HR and business leaders in a dynamic environment.
The predicted salary is between 36000 - 60000 £ per year.
A major energy provider in London seeks a talented Data Scientist to lead predictive workforce modelling initiatives. This role involves analysing large datasets, forecasting workforce demand, and collaborating with HR and business leaders.
Candidates should have a strong background in Python, statistical methods, and causal modelling, along with a relevant degree.
The position offers a competitive salary, a 7.5% bonus, and various benefits including annual leave and private medical cover.
Strategic Data Scientist: Workforce Modelling for Energy in City of London employer: UK Power Networks (Operations) Ltd
Contact Detail:
UK Power Networks (Operations) Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Strategic Data Scientist: Workforce Modelling for Energy in City of London
✨Tip Number 1
Network like a pro! Reach out to professionals in the energy sector on LinkedIn or at industry events. A friendly chat can open doors and give you insights that might just land you that Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those involving predictive modelling or workforce analytics. This will help us see your practical experience and how you can contribute to our team.
✨Tip Number 3
Prepare for the interview by brushing up on statistical methods and causal modelling. We want to see how you think, so be ready to discuss your approach to analysing large datasets and forecasting workforce demand.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Strategic Data Scientist: Workforce Modelling for Energy in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, statistical methods, and causal modelling. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about workforce modelling in the energy sector and how your background makes you the perfect fit for our team. Keep it engaging and personal!
Showcase Your Analytical Skills: In your application, include examples of how you've successfully analysed large datasets and forecasted demand in previous roles. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at UK Power Networks (Operations) Ltd
✨Know Your Data Inside Out
Make sure you’re well-versed in the datasets relevant to workforce modelling. Brush up on your Python skills and be ready to discuss how you’ve used statistical methods and causal modelling in past projects. Being able to explain your thought process clearly will impress the interviewers.
✨Showcase Your Collaboration Skills
This role involves working closely with HR and business leaders, so be prepared to share examples of how you’ve successfully collaborated in the past. Highlight any experiences where you’ve translated complex data insights into actionable strategies for non-technical stakeholders.
✨Prepare for Technical Questions
Expect some technical questions that test your knowledge of predictive modelling and forecasting techniques. Review common statistical methods and be ready to solve problems on the spot. Practising with mock interviews can help you feel more confident.
✨Understand the Energy Sector
Familiarise yourself with the energy industry and its current trends, especially regarding workforce dynamics. Showing that you understand the challenges and opportunities in this sector will demonstrate your genuine interest in the role and the company.
