Machine Learning Researcher

Il y a 2 mois


Paris, France Wiremind Temps plein

Since 2014, Wiremind has positioned itself as a **technical company** transforming the world of transport and events with a 360° approach combining **UX, software, and AI**.

Dynamic and ambitious, we strive to maintain our technical DNA which is the engine of our success. The company, profitable and self-financed since its creation 10 years ago, is mainly composed **of engineers and experts** and currently supports the growth of our **business model** based on "software-as-a-service" solutions.

**Your missions
***:
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.

You will be joining a team shaped to have all profiles necessary to constitute an autonomous department (devops, software and data engineering, data science, AIML, operational research).

As a research intern, you will have the opportunity to contribute to innovative projects at the intersection of deep learning and causal modeling.

You will be involved in topics such as:

- Leveraging causal inference methods like Regression Discontinuity Design or Orthogonal Learning to analyze and model complex demand patterns using time series data.
- Developing state-of-the-art deep learning architectures to improve the accuracy of current best models while maintaining causality and elasticity.
- Exploring the impact of pricing sequences on demand by modeling consumer behavior from a series of price changes instead of single adjustments.

**Technical stack**:
***:

- **Backend**:Python 3.11+ with SQLAlchemy
- **Orchestration**:Argo workflows over an auto-scaled Kubernetes cluster
- **Datastores**:Druid and postgresql
- **Common ML libraries/tools**: TensorFlow/Keras, LightGBM, XGBooost, Pandas, Dask, Dash, Jupyter notebooks
- **Model versioning and registry tool**: Mlflow
- **Gitlab / Kubernetes** for CI/CD
- **Prometheus/Grafana and Kibana** for operations

**Your profile**:

- Strong computer science **background in python**, with a keen interest for code quality and best practices (unit testing, pep8, typing)
- Knowledge about at least one major deep learning framework, e.g. tensorflow, pytorch
- A pragmatic, prod-oriented approach to ML: frequent, incremental gains beat a grand quest for perfection.

**What Would be a plus**:

- A first experience in a pricing-related domain
- A wish to puruse a career in academia with a PHD following the internship

**Our benefits**

By joining us, you will integrate:

- A self-financed startup with a strong technical identity
- Beautiful 700 m² offices in the heart of Paris (Bd Poissonnière)
- Attractive remuneration
- A caring and stimulating team that encourages skills development through initiative and autonomy
- A learning environment with opportunities for evolution ‍

You will also benefit from:

- 1 day of remote work per week
- A great company culture (monthly afterworks, regular meetings on technology and products, annual off-site seminars, team-building

**Our Recruitment Process**:

- An initial discussion with our Talent Acquisition Manager
- A technical test to be prepared
- A last interview at our offices to discuss your technical test with the Hiring Manager and meet with members of the team



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