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- Tasks: Develop and implement models for our energy supply business using Python.
- Company: Join a dynamic team focused on energy supply and risk management.
- Benefits: Enjoy competitive salary, stock options, biannual bonuses, and 28 days paid leave.
- Why this job: Be part of an innovative team making impactful decisions in the energy sector.
- Qualifications: 2+ years as a data scientist with strong Python and statistical skills required.
- Other info: Experience in the energy industry is a plus!
The predicted salary is between 43200 - 72000 £ 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.
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 holidays.
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Senior Data Scientist (Commodities) employer: Fuse Energy
Contact Detail:
Fuse Energy Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (Commodities)
✨Tip Number 1
Make sure to showcase your experience with Python and data science tools like Pandas, NumPy, and SciPy in your conversations. Highlight specific projects where you've successfully implemented models, as this will demonstrate your hands-on expertise.
✨Tip Number 2
Stay updated on the latest trends and regulations in credit risk management. Being knowledgeable about current industry developments will not only impress us but also show your commitment to the field.
✨Tip Number 3
Prepare to discuss how you collaborate with engineering teams. We value strong communication skills, so be ready to share examples of how you've worked effectively with cross-functional teams in the past.
✨Tip Number 4
If you have any experience in the energy industry, make sure to bring it up! This can set you apart from other candidates and show that you understand the unique challenges and opportunities in our sector.
We think you need these skills to ace Senior Data Scientist (Commodities)
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your 2+ years of experience as a data scientist. Detail specific projects where you developed and implemented models, especially in the energy sector if applicable.
Showcase Technical Skills: Clearly list your programming skills in Python and your experience with data science tools like Pandas, NumPy, and SciPy. Provide examples of how you've used these tools in past projects.
Demonstrate Statistical Knowledge: Include specific examples of your statistical and modeling skills. Discuss any relevant methodologies or techniques you have applied in your previous roles.
Communicate Effectively: Since strong communication and collaboration skills are required, consider including examples of successful teamwork or projects where you effectively communicated complex data insights to non-technical stakeholders.
How to prepare for a job interview at Fuse Energy
✨Showcase Your Statistical Skills
Since the role emphasizes a strong background in statistics, be prepared to discuss your experience with statistical models. Bring examples of how you've applied these skills in previous projects, especially in relation to risk management.
✨Demonstrate Your Programming Proficiency
Highlight your programming skills in Python and familiarity with data science tools like Pandas, NumPy, and SciPy. Consider discussing specific projects where you utilized these tools to solve complex problems.
✨Understand the Energy Sector
If you have experience in the energy industry, make sure to mention it. Discuss any relevant projects or insights you have that relate to energy supply and credit risk management, as this will show your understanding of the sector.
✨Prepare for Collaboration Questions
Given the collaborative nature of the role, be ready to share examples of how you've worked effectively with engineering teams or other departments. Highlight your communication skills and how they contributed to successful project outcomes.
