Job description

Duties and Responsibilities

  • Familiarize with Ensign’s business domain and objectives to implement cyber security analytics solutions that meet internal business requirements and the needs of industry partners and customers
  • Develop, evaluate, tune, deploy, maintain and document production-grade data analytics models that provide cyber security insights
  • Work on large volume of raw, structured and unstructured data from internet traffic, logs and other forms of data sources using Apache Spark, MPP DB, NoSQL, Hadoop, Scala, Python, R, Tableau etc on daily basis
  • Evaluate potential solutions relating to data analytics and make recommendations to solve business problems
  • Liaise and work with in-house developers, data engineers, big data architects, visualization engineers and project managers to better understand the requirements of developing, deploying and productizing models
  • Ensure the analytics models are running in optimal condition and perform trouble-shooting when the models are having issue
  • Advocate and ensure security best practices
  • Manage technical data science projects and improve data science workflow and processes periodically
  • Coach and review the work of junior data scientists
  • Able to manage and resolve difficult and complex technical problems with minimal supervision


  • Minimum Degree in Statistics, Data Science, Mathematics, Computer Science, Engineering or any other related quantitative field
  • Minimum 5 years of experience working in a data science position, preferably in the cyber security industry and has worked with security logs/network data
  • Experience and expertise in probability and statistical modelling, inclusive of machine learning, experimental design, evaluation and optimization
  • Proficiency in Scala, Python, R, Java, Spark and SQL, among others
  • Ability to perform rapid prototyping and proof of concept using visualization and dashboarding tools such as Tableau
  • Experience in implementing projects using machine learning and deep learning frameworks using tools such as TensorFlow, Keras, Caffe, MxNet, Spark, Hadoop, R, pandas
  • Solid technical background with hands-on experience in conceptualizing, designing, implementing and deploying statistical or machine learning models in the big data environment (e.g. Hadoop)
  • Excellent client-facing and internal communication skills
  • Solid organizational skills including attention to detail and multi-tasking
  • Team-player, result-oriented, proactive, self-driven, requiring minimal supervision
  • Creative problem-solving skills, highly organized, with ability to handle multiple simultaneous tasks, prioritize and meet tight deadlines

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