Statistician or Data Scientist

Om stillingen

We are a leading Data Science company with a focus on algorithmic trading in the financial markets. We hire exceptional talent in the fields of Mathematics, Physics and Computer Science to help build and develop our sophisticated computing and research platform. We’re a meritocratic, non-hierarchical community of self-starters with a hunger for new ideas and healthy debate, our culture celebrates innovative thinking and challenging of the status quo. We have offices in Norway, United Kingdom and the US.

Statistician or Data Scientist, Oslo

Abelee is growing quickly and looking for Statisticians or Data Scientists to join our team in Oslo. This is a senior level role open to university graduates with 1-3 years working experience or a PhD (or higher) within statistics, data science or mathematical finance. Working experience, or a degree, within quantitative or mathematical finance is not required. We are looking for candidates with experience working and/or analysing complex data, with a strong foundation within quantitative methods.

We offer a unique opportunity to gain in-depth exposure to the field of quantitative finance working with high dimensional, real time and high frequency data.

What you will do

  • Analysing and developing real time models for trading, pricing, risk assessment and uncertainty 
  • Work in close collaboration in a small team of highly educated analysts and developers.
  • Work on problems that will have a significant impact on daily operations. 
  • Work in an agile environment, where good ideas and analysis, can lead to implementation and production code the following day. 

Ideal candidates are dynamic, self-starters that are passionate about data, with a desire to understand the inner workings of complex systems, and also self-critical with an attention to the details.

About you

  • PhD in statistics or data science OR master’s degree in quantitative fields such as statistics, data science, mathematical finance or economics with 1-3 years of relevant working experience. 
  • Experience analysing complex data (as part of the degree or equivalent work experience). 
  • Proficiency in graduate level of mathematical statistics, such as estimation theory, resampling/bootstrapping, Bayesian statistics, nonparamteric methods, etc.  
  • Proficiency within quantitative methods for applied data analysis and statistics. 
  • Basic knowledge of time series analysis, stochastic analysis, mathematical finance and standard methods within machine learning. 
  • Hands on programming experience in scripting (e.g. Python or R) and/or compiled languages (e.g. Java/C++).
  • An ability to communicate advanced concepts in a concise and logical way, and preferable experience from working in interdisciplinary groups.
  • Excellent quantitative problem-solving and analytical skills.
  • Attention to detail and self-critical thinking.
  • Self-motivated and with ability to work with minimal supervision

What we can offer

  • Competitive salary and benefits, including a pension plan, insurance and more.
  • Opportunity to actively use all the tools and everything you have learned every day. 
  • To be in an environment where research is highly valued, that strives to be at the forefront and where there are good opportunities to further develop within the field. 
  • An opportunity to test your analytical abilities on some of the hardest and most challenging problems with the market providing immediate feedback. 
  • New challenges and professional growth in start-up backed by Aker ASA.
  • Brand new office centrally located. With a fitness room, wardrobe, cycle garage and maintenance, breakfast and lunch served by Restaurant Haakon.

We value diversity of thought, backgrounds, experiences and perspectives and we’re looking for those who have innovative ideas, entrepreneurial qualities, and enjoy tackling new challenges and solving intellectual problems.

 Please submit your application with CV and cover letter (max. 1 page) to Applications will be accepted until 31 July 2021 and reviewed on a continuing basis.

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