Junior Data Analyst

Permanent position

About SpaceAble

The advent of New Space raises several issues of efficiency, security and sustainability (Space Situational Awareness – SSA), rapidly transforming the Low Earth Orbit (LEO) paradigm.
At the heart of the space community in Europe and internationally, SpaceAble is a French startup which, through its bold scientific approach, has set itself the mission of ensuring the safety of space operations and contributing to sustainability in LEO through critical space data.
To achieve this, we are developing an SSA predictive risk assessment software platform and an autonomous on-demand inspection satellite.
SpaceAble is composed of a multidisciplinary team (data, tech, cybersecurity, space engineering, legal, partnerships) with origins, experiences and personalities as diverse and enriching as each other!

Job: Position is open to people with disabilities
Contract: Permanent position
Position Type: Full time
Location: Paris 10th Arrondissement, Toulouse
Experience: 1 year
Travel: Occasional
Salary: Commensurate with experience


SpaceAble is looking for a junior data analyst as it builds its AI segment. The main responsibility will be to take over, within this segment, everything having to do with space data creation, management, and preparation. This key segment will work closely with a scientific team, several external partners and the software platform’s development team.

  • Work with our scientists to identify and analyze the data
  • Develop algorithms to meet the needs of our users
  • Work with developers to improve the reliability of the data and its use
  • Help to implement good AI and data practices and consolidate our body of knowledge
  • Be proactive in the choice of algorithms and data preprocessing as well as the management and growth of the AI segment.

Job requirements

Required skills

  • Independence and methodology
  • In software development 
    • Python 3, Pytorch or Eigen (Enria) for industrialization, Pytorch-lightning or Frastai for prototyping.
    • Capacity to pragmatically manage a large quantity of heterogeneous data
    • The data pipelines will need to be written for data in various formats
  • In statistical modeling
    • Machine Learning: SVM, adaptive filters
    • Deep learning: convolutive network, fully connected, partial knowledge of networks for the analysis of temporal series (LSTM, RNN, TCN, etc.)
  • Mathematics
    • Principle of gradient descent, optimizer and scheduler choices.
    • Constraint optimization (Lagrangien/KKT)
    • Knowledge of L1 and L2 regularization effects
  • Data analysis
    • Principal component analysis (linear and non-linear), dimension reduction
    • Management of data sets and their equilibrium
    • Modelization limits evaluation based on practice data (overfitting, outlier)
  • Knowledge of the following information sources: IEEE, Kaggle, Gitlab

Optional Skills

  • Project management
  • Interest in technology, science, and space news
  • Tensorboard for visualization
  • Capable of dealing with potentially strategic and sensitive matters
  • Interest in open-source culture (forum and git)
  • Culture of OS and GPU calculations
  • Introduction to unsupervised learning: (GMM model, KNN, etc.)

We are waiting for you