Data Science Intern & PhD

Our job every day is to protect the data and critical assets of businesses world-wide by discovering hidden vulnerabilities… before the bad guys do!

At CybelAngel, we see beyond perimeters to protect businesses from the most critical cybersecurity threats. Fortune 500 Global to mid-size companies world-wide, trust CybelAngel’s global team of approximately 200 team members to protect their businesses from digital threats. With a combination of advanced machine learning, cyber analysis expertise, and a powerful suite of software solutions, CybelAngel detects and resolves our client’s potential threats, long before they can fall into the hands of cyber criminals.

Our capabilities expand every day to uncover new risks, detect more threats, protect more clients, and create new possibilities for our employees.

The goal of the Data Science team is to build Artificial Intelligence models to improve our product.

These models enable the company to leverage data by correctly storing, interpreting and understanding patterns out of it. 

We’re looking for a data scientist intern to extend the team. The goal of this internship is to prepare together the PhD CIFRE offer.

Job Description

We process billions of documents every day to extract leaks of relevant data about our customers.

Introducing intelligence at the various levels of our processing pipeline is therefore a crucial issue for CybelAngel. Our Data Science team’s mission is to make our filtering algorithms as intelligent as possible, in order to optimize and facilitate the processing of security incidents.

These filtering algorithms are machine learning based algorithms. It is important to always try to improve these models. Several possibilities exist and can be tried, like deep learning, side learning (auxiliary tasks), multi-objective loss functions. The goal of this internship is to analyze and prepare all the possible improvements in order to have a strong basis for starting the PhD.

Your goals

• Study and understand our models (supervised machine learning, unbalanced data, large volume)
• Optimize specific parameters (possibly non-derivative optimization or multi-objective optimization)
• Share & document, so every experiment can be reproduced
• Depending on results, release to production
• Explore and study state-of-the-art algorithms to serve as a strong basis for the doctorate

Our technical stack

• Dev: Python, Pandas, Matplotlib, Sklearn, Xgboost
• CI/CD: Git, Gitlab, Gitlab CI
• Ops: Kubernetes, GCP

Requirements

Requirements

• Artificial Intelligence, Data Science or mathematical master (M2)
• Will to continue with a PhD

Benefits

Benefits

💰 Salary: 1200€ per month

🍱 Debit card for paying for lunch, with company contribution.

💛 Very friendly and benevolent atmosphere 

Your hiring journey

• 30’ call with Pierre, recruiter, to discuss expectations from both ends
• 30’ call with Fabien, Data Science Team Lead, to discuss context and projects and to evaluate mission fit
• 120’ Technical exercise and restitution to the whole Data Science team to assess your skills