- Big Data, Finance
- Od 15 do 50 zaměstnanců
Intern Data Scientist: Seasonal Adjustment and Dynamic Factor Models on High Frequency Alternative Data
- Stáž (6 měsíc/měsíce/měsíců)
- Možnost pracovat příležitostně z domova
- Vzdělání: Magisterský stupeň vzdělání
- zkušenosti: < 6 měsíců
Tato pozice byla obsazena!
Who are they?
QuantCube analyses billions of alternative data points in real time, using artificial intelligence and big data analytics to deliver insights ahead of the market – giving users an edge in their investment strategies.
Today we are the global leader in macroeconomic intelligence nowcasting and in pinpointing macro regime change. Our vision is to become the standard point of reference for macroeconomic, sector, corporate and environmental intelligence. By delivering timely, comprehensive and actionable economic insights we empower users within financial institutions, corporates and public bodies to reach their financial performance and sustainability goals.
Headquartered in Paris, QuantCube employs a diverse international team of economists, quant analysts and data scientists with expertise in multilingual NLP, deep learning and machine learning techniques. The company’s shareholders include Moody’s and Caisse des Dépôts and its R&D in computer vision has been partially funded by the European Space Agency (ESA) and French government space agency CNES.
QuantCube Technology’s product consists in providing real-time economic indicators to different economic actors, whether it be private investors like hedge funds or banks or public institutions. Those alternative data may suffer from seasonal biases at daily, weekly and monthly frequencies. Creating seasonally adjusted series at high frequencies raises theoretical challenging issues. There are alternative methods to test, improve or even modify to achieve such a project which requires a good knowledge of time series analysis or spectral theory (Fourier and Signal extraction theories). Once such adjustment is realized it is then possible to build high frequency series modelling such as Industrial Production and even GDP using cutting edge linear or non-linear State Space Bayesian Models. The Macro Team is therefore looking for an intern with econometric and machine learning skills with a strong interest in bayesian learning and time series analysis.
The assignments you will be working on include:
- Designing the most robust methodology to create high frequency alternative data seasonally adjusted series based on cutting edge research
- Create high frequency US and China macro series
- Using and improving QuantCube pipelines with state-of-the-art algorithms
- Taking part in the production adaptation of the codes
You will have the opportunity during these assignments to quickly gain responsibility: to lead a project from A to Z from pre-processing to modelling ; benefiting from weekly updates on the global economy ; to communicate directly with our IT and Data Science teams who are at the forefront of their field ; present your work to the whole team at the end of the internship.
We are a close-knit, friendly and multicultural team. We are looking for motivated people to join the adventure and participate in the development of QuantCube.
- Strong level in python, in mathematics and statistics
- Mastery of Time Series Analysis, Spectral Analysis, interest in State Space Modelling and Signal Extraction theories
- Fluent in English
QuantCube recruits and recognises all talents
- Meet the recruiter and Data Scientist Specialist (30 min)
- Technical interview (1h)
- Meet the co-founders (30 min)