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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 fully expensed tech.
- 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; 28 days paid leave included.
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:
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Develop and implement models for our energy supply business using Python and other data science tools.
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Identify, analyze, and mitigate credit risk.
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Conduct data analysis and modeling to support risk management decisions.
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Stay current with industry developments and regulations related to credit risk management.
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2+ years of experience as a data scientist.
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Strong programming skills in Python and experience with data science tools such as Pandas, NumPy, and SciPy.
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Strong statistical and modeling skills.
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Strong communication and collaboration skills.
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Experience in the energy industry is a plus.
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Competitive salary and a stock options sign-on bonus
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Biannual bonus scheme
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Fully expensed tech to match your needs!
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28 days paid annual leave per year including public holiday
Senior Data Scientist (Commodities) employer: Fuse Limited
Contact Detail:
Fuse Limited 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 experience as a data scientist, particularly any projects or roles that involved developing models for energy supply or credit risk management. Use specific examples to demonstrate your skills.
Showcase Technical Skills: Clearly outline your programming skills in Python and your familiarity with data science tools like Pandas, NumPy, and SciPy. Mention any relevant projects where you utilized these tools effectively.
Demonstrate Statistical Knowledge: Since the role requires strong statistical and modeling skills, include any relevant coursework, certifications, or projects that showcase your expertise in statistics and data analysis.
Tailor Your Communication: Given the importance of communication and collaboration in this role, ensure your application reflects your ability to work well in teams. Mention any experiences where you successfully collaborated with engineering or other teams.
How to prepare for a job interview at Fuse Limited
✨Showcase Your Statistical Expertise
Since the role requires a strong background in statistics, be prepared to discuss your experience with statistical models and techniques. Bring examples of how you've applied these skills in previous projects, especially in relation to risk management.
✨Demonstrate Your Programming Skills
Highlight your proficiency in Python and data science tools like Pandas, NumPy, and SciPy. Be ready to discuss specific projects where you utilized these tools to develop models or conduct data analysis.
✨Understand the Energy Sector
Familiarize yourself with current trends and regulations in the energy industry, particularly those related to credit risk management. Showing that you are knowledgeable about the sector will demonstrate your commitment and readiness for the role.
✨Emphasize Collaboration and Communication
As you'll be working closely with the engineering team, it's crucial to showcase your collaboration and communication skills. Prepare examples of how you've successfully worked in teams and communicated complex data insights to non-technical stakeholders.
