Associate Data Scientist

Ensign is hiring !

Key Objective: Familiarize with Ensign’s business domain and goals. Design and implement cyber security solutions that meet internal business requirements and the needs of industry partners and customers

Responsibilities:

• Model Development:
  • Design, develop, and optimize machine learning solutions tailored to solve specific business problems in the areas of Cyber Security.
  • Collaborate domain experts to understand structured or unstructured data, define features, and build models using tools such as TensorFlow, PyTorch, or Scikit-Learn.
• Model Deployment:
  • Deploy and maintain production-grade machine learning models in production
  • Ensure the 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 Machine Learning 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
• Knowledge in probability and statistical modelling, inclusive of machine learning, experimental design, evaluation and optimization
• Knowledge in Python, Spark, Java or Scala, and SQL among others
• Ability to perform rapid prototyping and proof of concept
• 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 Kubernetes and ability to develop and deploy containerized models that leverage on cloud resources or on prem.
• Team-player, result-oriented, proactive, self-driven, requiring minimal supervision
• Prior knowledge or interest in the Cyber Security domain will be preferred.