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Senior Data Scientist - Cybersecurity



Data Science
Posted on Sunday, July 9, 2023

What if you can safeguard the future of IoT?

MicroSec is building cyber-defense technology to protect the future of IoT. If you are looking for a challenging and interesting role, be part of the Microsec journey.

Successful applicants will be responsible for designing, developing, and implementing machine learning applications and services for MicroSec’s IoT cybersecurity products. They will follow agile scrum methodologies to establish needs from Product Owners, and help with the self-organization of their development team, guiding junior team members. There will be a broad range of problems to solve, such as cryptographic implementations, machine learning, IoT communication, and DevOps-related issues.


  • Design, develop and deploy AI/ML solutions in Cybersecurity domain
  • Developing security measures, which should be implemented against possible cyber threats, in the system design phase (ex. Automatic response algorithm for cyber threats)
  • Develop and maintain tools and techniques for detecting and analyzing cyberattacks including malware, DDoS etc via, custom scripts, plugins, sandboxes etc.
  • Conduct research and analysis on network traffic and payloads to identify and analyze malicious activity and threats.
  • Collect and prepare data sets for use in machine learning models, ensuring that they are representative, accurate, and relevant to the malware threats being analyzed.
  • Involve in developing key AI/ML capabilities in areas such as anomaly detection, malware recognition, network analysis and deep packet inspection
  • Developing host-based and network-based cyber security tool
  • Continuously assess the effectiveness of existing security solutions and technologies, and make recommendations for improvements based on analysis of real-world threats and trends.
  • Review and analyze security vulnerabilities for the IoT & OT networks, application systems, hardware infrastructure and emerging technologies to improve the enterprise information security posture.
  • Create proof of concept code to demonstrate the identified security issues and detection mechanism
  • Work closely with the Engineering teams (frontend and backend) to implement, deploy, and maintain production systems
  • Write thorough documentation
  • Effectively communicate highly technical results to various teams
  • Manage the Data Science team members including interns and their hiring


  • At least a PhD or Master’s degree in any quantitative discipline: Applied Mathematics, Computer Science, Statistics, etc.
  • At least 4+ years of Cyber Security Research experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience
  • At least 4-5 years of experience in Python and relevant frameworks such as Django and Flask
  • At least 5 years of experience in development for Linux-based platforms.
  • Familiar with typical enterprise security solutions, such as Endpoint Security, Identity & Access Control solutions, Network Security, Analytics solutions, Data Loss Prevention or Vulnerability and Compliance.
  • In-depth knowledge of cyber-attack analysis tools and techniques, including dynamic and static analysis, reverse engineering, and memory forensics.
  • Experience with sandboxing tools and virtual machines.
  • Monitoring and analyzing network traffic and packet captures
  • Understanding of Operating System Kernels
  • At least 2-3 years of experience in libraries and services including SQLAlchemy, RabbitMQ, PostgreSQL, InfluxDB.
  • Experience with Edge Machine Learning, Embedded ML, and TinyML
  • Experience of Machine learning applications for intrusion and anomaly detection
  • Experience in working with Docker, Docker Swarm, Kubernetes, and Git CI/CD
  • Experience in OpenSSL, TLS configurations and Public Key Infrastructure
  • Working experience with socket programming, TCP/UDP, Network interfaces, low-level Kernel interfaces, System I/O calls, Systemd services.
  • Experience with databases of different types, such as SQL, time-series and key-value stores
  • DevOps experience for secure continuous integration and deployment
  • Experience in implementing REST APIs, with specifications written in OpenAPI / Swagger or Postman
  • Full development lifecycle experience for the data analytics solutions, such as business & data understanding, data preparation, model development, visualization, validation, and deployment.
  • A history of working within an agile environment, either Scrum or similar, with a focus on responsible, customer-focused delivery
  • Ability to clearly document work, through well-defined specifications, code comments, user- and developer-guides
  • A broad portfolio of algorithms, languages and paradigms, demonstrating