Senior Weather Analyst/ml Researcher

at Jane Street · Quant · London, United Kingdom · Quantitative Trading

Research role focused on applied research in weather prediction, embedded within a commodities trading desk. Requires strong programming skills (Python), expertise in atmospheric science topics, and experience with AI models. The role involves challenging the limits of atmospheric predictability and exploring new research directions.

What you'd actually do

  1. work on applied research on our weather team, embedded within the commodities trading desk
  2. challenge the limits of atmospheric predictability
  3. push in new and unknown directions while maintaining clarity of purpose

Skills

Required

  • Masters degree in Atmospheric Science or related field
  • Python programming
  • sub-seasonal predictability
  • data assimilation
  • numerical weather prediction
  • tropical variability
  • synoptic meteorology
  • renewable energy forecasting
  • gridded data analysis
  • observational data analysis
  • satellite data analysis
  • quantitative research
  • English fluency

Nice to have

  • AI models

What the JD emphasized

  • Must be a strong programmer
  • Experience with AI models preferred
  • Have good taste in research
  • challenge the limits of atmospheric predictability
  • push in new and unknown directions

Other signals

  • applied research
  • commodities trading desk
  • atmospheric predictability
  • new and unknown directions
Read full job description

About the Position

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

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