CONTEXT
At Wiremind, the Data Science team is responsible for the development, monitoring and evolution of all ML-powered forecasting and optimization algorithms in use in our Revenue Management systems. Our algorithms are divided in 2 parts:
A modelling of the unconstrained demand using ML models (e.g. deep learning, boosted trees) trained on historical data in the form of time-series
Constrained optimizations problems solved using linear programming techniques
The team is now entering a scaling phase where we will face the challenge to stay agile in terms of innovation while supporting and closely monitoring deployed algorithms.
This rapid growth comes with a multiplication of data sources and deployed predictive models. In order to maintain high prediction accuracies and ascertain data quality, we are looking for a highly motivated data scientist intern to join our team.
WHAT YOU WILL DO
You will be joining a team shaped to have all profiles necessary to constitute an autonomous departement (devops, software and data engineering, data science, AIML, operational research).
There, you will leverage state-of-the-art AI/ML methods and ironclad validation processes to deliver robust, interpretable prediction systems.
As a Data scientist intern, you will work on the following topics:
Designing/training of new models (neural networks or decision trees) to improve our current models in production
Tackling railway demand specific challenges: imbalanced data, skewed data distributions, features engineering
Performing in-depth model evaluation: to properly assess model performance and comparison with other models.
Taking part in the improvement of our training pipeline framework.
Survey state of the art models / practices in our domain specific applications.
TECHNICAL STACK
Python 3.7+
KubeFlow over an auto-scaled Kubernetes cluster for orchestration
Druid as datastore
Common ML libraries: TensorFlow/Keras, LightGBM, XGBooost, Pandas, Dask, Dash
Gitlab for continuous delivery
WHAT MATTERS TO US
Current studies (at least Master I) related to the following fields: data science, computer science, applied mathematics.
Good understanding of basic machine learning tasks (classification, regression) and mathematical concepts behind it
Good understanding of basic evaluation metrics : accuracy, recall, precision, RMSE,….
Hands-on experience with python language and standard data tools: Pandas, NumPy
Strong curiosity and desire to learn
WHAT WOULD BE A PLUS
Strong computer science background in Python,
A good experience in model development (Kaggle, class or personal projects,..)
The position is based in the city center of Paris (Etienne Marcel metro station). We offer attractive pay packages depending on profile, closely linked to your performance and the growth of the company.
Tyto společnosti rovněž nabírají pracovníky na pozici "{profese}".