Key Objective: Familiarize with Ensigns business domain and goals. Design and implement cyber security solutions that meet internal business requirements and the needs of industry partners and customers
Responsibilities:
- Data Analysis and Threat Detection: Analyze large datasets of raw, structured and unstructured data from internet traffic, logs and other forms of data sources to identify patterns, anomalies and cyber security insights indicative of cyber threats, using user behavior analytics and other methods.
- Model Development: Develop, evaluate, tune, deploy and maintain production-grade machine learning models for intrusion detection, malware analysis, fraud detection, and user behavior anomaly detection, deepfake and fake news detection among other used cases. Ensure the analytics models are running in optimal condition by participating in purple teaming exercises and perform trouble-shooting, finetuning and retraining in situations of model drifts.
- Collaboration and Communication: Work with cybersecurity teams (developers, data engineers, big data architects, visualization engineers and project managers) and stakeholders to integrate data science models and communicate findings to both technical and non-technical stakeholders.
- Continuous Improvement: Contribute to the ongoing improvement of cybersecurity strategies by leveraging data science approaches and staying updated on the latest trends. Evaluate potential solutions relating to data analytics and make recommendations to solve business problems. Advocate and ensure security best practices.
Requirements:
- Degree in Statistics, Data Science, Mathematics, Computer Science, Engineering or any other related quantitative field
- 3 to 5 years of experience working in a data science position, preferably in the cyber security industry and has worked with security logs/network data
- Knowledge in probability and statistical modelling, inclusive of machine learning, experimental design, evaluation and optimization
- Proficiency in Python, Spark, Java or Scala, and SQL among others
- Ability to perform rapid prototyping and proof of concept using visualization and dashboarding tools
- Knowledge in machine learning and deep learning frameworks and tools such as TensorFlow, Keras, Caffe, MxNet, Spark, Hadoop, R, pandas, sklearn
- Knowledge of cloud (AWS, Azure or GCP) and ability to develop and deploy containerized models that leverage on cloud resources or on prem.
- Excellent client-facing and internal communication skills
- Solid organizational skills including attention to detail, critical thinking and multi-tasking
- Team-player, result-oriented, resourceful, proactive, self-driven, requiring minimal supervision
- Creative problem-solving skills, highly organized, with ability to handle multiple simultaneous tasks, prioritize and meet tight deadlines
- Prior knowledge or interest in the Cyber Security domain will be preferred.
