We are seeking motivated and passionate talents eager to accelerate their professional growth in data science and network security, contributing to innovative projects and solutions while helping to protect our users, their infrastructure and data.
Design, develop, and deploy machine learning models for anomaly detection in DNS traffic, identification of malicious behaviors, and prediction of system failures.
Analyze complex time series data from servers to identify suspicious patterns, abnormal trends, and anticipate potential incidents.
Optimize and maintain data pipelines to ensure efficient processing of large volumes of DNS data and security metrics in real-time or near-real-time.
Create and maintain analytical dashboards and data visualizations to effectively communicate security insights to both technical and non-technical teams.
Stay up-to-date with the latest data science techniques applied to cybersecurity, emerging anomaly detection methods, and evolving threats in the DNS ecosystem through continuous research and professional development.
Collaborate with other team members to refine models, reduce false positives, and continuously improve the quality of generated alerts.
You’ll be great for this role if you have these qualifications:
Strong experience in Python for data science, with proficiency in libraries such as pandas, scikit-learn, TensorFlow/PyTorch, and time series analysis tools (e.g., Prophet, statsmodels).
Strong understanding of machine learning techniques, particularly anomaly detection, classification, clustering, and predictive modeling applied to security use cases.
Experience working with data processing frameworks and tools (e.g., Airflow, PostgreSQL, Dask, Redis).
Good knowledge of networking protocols (DNS, DHCP, TCP, UDP, IP, etc.) and cybersecurity concepts (threat intelligence, malware behavior, attack patterns, IoCs).
Excellent problem-solving and analytical skills with the ability to translate complex data into actionable security insights.
Ability to work both independently and as part of a cross-functional team.
Strong communication skills to present findings and recommendations to both technical and non-technical stakeholders.
Bonus: Experience with data visualization tools (e.g., Plotly, Grafana) and building dashboards.
Bonus: Participation in Kaggle competitions, conferences, CTFs, and personal projects.
Fluent in French.
1st interview with TA and Head of Cybersecurity
Interview with the CTO
Meet William, Head of Engineering
Meet Jean Yves, CTO & Founder
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