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- Tasks: Conduct applied research on weather patterns and collaborate with a dynamic trading team.
- Company: Join a leading firm at the forefront of weather analysis and commodities trading.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Why this job: Make a real impact in atmospheric science while pushing the boundaries of predictability.
- Qualifications: Master's degree in Atmospheric Science, strong programming skills, and experience with AI models.
- Other info: Engage in a fast-paced, collaborative environment with diverse teams.
The predicted salary is between 36000 - 60000 £ per year.
We are looking to hire a strongly motivated individual who is excited to work in a fast paced, collaborative environment. We are looking for someone who wants to work on applied research on our weather team, embedded within the commodities trading desk. We invite graduate students nearing graduation, both early career and experienced academics, and industry professionals to apply.
About You
- Masters degree (minimum) in Atmospheric Science or related field
- Must be a strong programmer, with excellent python skills for data analysis
- Expertise in relevant topics such as: sub-seasonal predictability, data assimilation and numerical weather prediction, tropical variability, synoptic meteorology, renewable energy forecasting
- Experience using gridded data, observational data and satellite data to drive quantitative research in academia or industry
- Experience with AI models preferred
- Have good taste in research. The problems you will work on will aim to challenge the limits of atmospheric predictability.
- You should be comfortable pushing in new and unknown directions while maintaining clarity of purpose
- Think and communicate precisely and openly. We believe great solutions come from the interaction between diverse groups of people across the firm
- Fluency in English required
Senior Weather Analyst/ML Researcher employer: Jane Street
Contact Detail:
Jane Street Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Weather Analyst/ML Researcher
✨Tip Number 1
Network like a pro! Reach out to professionals in the weather and ML fields on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those related to atmospheric science or data analysis. This will give you an edge and demonstrate your expertise.
✨Tip Number 3
Prepare for interviews by brushing up on relevant topics like sub-seasonal predictability and AI models. Be ready to discuss how your experience aligns with the challenges of atmospheric predictability.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Weather Analyst/ML Researcher
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming prowess, especially in Python. We want to see how you can use your skills in data analysis to tackle the challenges we face in weather prediction.
Tailor Your Application: Don’t just send a generic CV and cover letter. Take the time to align your experience with our job description. Show us how your background in atmospheric science and relevant research makes you the perfect fit for our team.
Be Clear and Concise: When writing your application, clarity is key. We appreciate straightforward communication, so make sure your points are easy to understand and directly related to the role.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss any important updates from our team.
How to prepare for a job interview at Jane Street
✨Know Your Stuff
Make sure you brush up on your atmospheric science knowledge and relevant programming skills, especially in Python. Be ready to discuss your experience with data analysis and any specific projects you've worked on that relate to sub-seasonal predictability or numerical weather prediction.
✨Showcase Your Research Taste
Prepare to talk about your research interests and how they align with the company's goals. Think about the challenges in atmospheric predictability and be ready to share your ideas on pushing boundaries in this field. This shows you're not just knowledgeable but also passionate about the subject.
✨Communicate Clearly
Practice articulating your thoughts clearly and concisely. Since the role involves collaboration, being able to communicate complex ideas simply is key. Consider doing mock interviews with friends or colleagues to refine your communication style.
✨Embrace Collaboration
Highlight your experience working in teams and how you value diverse perspectives. The company thrives on collaboration, so sharing examples of successful teamwork or interdisciplinary projects can really set you apart during the interview.