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- Tasks: Develop and implement models for our energy supply business using Python.
- Company: Join a dynamic team focused on innovative energy solutions.
- Benefits: Enjoy competitive salary, stock options, and fully expensed tech.
- Why this job: Be part of a collaborative culture that values your input and growth.
- Qualifications: 2+ years in quantitative research; strong Python and data science skills required.
- Other info: 28 days paid leave plus public holidays; bonus schemes available.
The predicted salary is between 36000 - 60000 £ per year.
We are currently seeking a Senior Data Scientist with a strong background in statistics to join our team. The role will be responsible for developing and implementing models for our energy supply business. As a Senior Data Scientist, you will work closely with our engineering team to ensure the accuracy and effectiveness of our models.
Responsibilities:
- Develop and implement models for our energy supply business using Python and other data science tools.
- Identify, analyze, and mitigate credit risk.
- Conduct data analysis and modeling to support risk management decisions.
- Stay current with industry developments and regulations related to credit risk management.
Minimum Requirements:
- 2+ years of experience as a data scientist.
- Strong programming skills in Python and experience with data science tools such as Pandas, NumPy, and SciPy.
- Strong statistical and modeling skills.
- Strong communication and collaboration skills.
- Experience in the energy industry is a plus.
Benefits:
- Competitive salary and a stock options sign-on bonus
- Biannual bonus scheme
- Fully expensed tech to match your needs!
- 28 days paid annual leave per year including public holiday
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Quantitative Researcher employer: Fuse Energy
Contact Detail:
Fuse Energy Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher
✨Tip Number 1
Familiarise yourself with the latest trends and developments in the energy sector. This will not only help you understand the context of your role but also demonstrate your genuine interest in the industry during interviews.
✨Tip Number 2
Brush up on your Python skills, especially with libraries like Pandas, NumPy, and SciPy. Consider working on personal projects or contributing to open-source projects to showcase your programming abilities and practical experience.
✨Tip Number 3
Network with professionals in the quantitative research and energy sectors. Attend relevant conferences, webinars, or meetups to connect with potential colleagues and learn more about the challenges they face in their roles.
✨Tip Number 4
Prepare for technical interviews by practising common quantitative research problems and case studies. Being able to articulate your thought process and problem-solving approach will set you apart from other candidates.
We think you need these skills to ace Quantitative Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a quantitative researcher or data scientist. Emphasise your programming skills in Python and familiarity with data science tools like Pandas, NumPy, and SciPy.
Craft a Strong Cover Letter: In your cover letter, explain why you are interested in the role and how your background in statistics and experience in the energy industry (if applicable) make you a great fit for the team.
Showcase Relevant Projects: Include specific examples of projects where you developed and implemented models, particularly those related to risk management or credit risk. This will demonstrate your practical experience and problem-solving skills.
Highlight Communication Skills: Since collaboration with the engineering team is crucial, mention any experiences that showcase your strong communication and teamwork abilities. This could include working on cross-functional projects or presenting findings to stakeholders.
How to prepare for a job interview at Fuse Energy
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and data science tools like Pandas, NumPy, and SciPy. You might be asked to solve a technical problem or explain how you've used these tools in past projects.
✨Demonstrate Your Statistical Knowledge
Since the role requires strong statistical and modelling skills, brush up on key concepts and be ready to discuss how you've applied them in real-world scenarios. Consider bringing examples of models you've developed.
✨Understand the Energy Sector
Familiarise yourself with current trends and regulations in the energy industry. Showing that you have a grasp of the sector will demonstrate your commitment and interest in the role.
✨Prepare for Collaboration Questions
As the role involves working closely with an engineering team, be ready to discuss your collaboration experiences. Think of examples where you successfully worked in a team to achieve a common goal.
