We’re looking for a candidate to fill this position in an exciting company.
Evaluate potential solutions relating to data analytics and make recommendations to solve business problems.
Liaise and work with in-house threat analysts, threat researchers, malware analysts, developers, data engineers, big data architects, visualization engineers and project managers to better understand the requirements of developing, deploying and productizing data science 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 workflow and processes periodically.
Coach and review the work of junior data scientists and participate in technical interviews of potential new hires.
Able to manage and resolve complex technical problems with minimal supervision.
Participate and provide technical leadership in the scoping of customer projects
Plan and lead the delivery of projects and front customer related technical discussion
Actively engage various stakeholders and Business Units to solicit used cases and lead the end-to-end delivery of solutions to meet the needs of identified used cases
Lead the exploration and application of SOTA data science techniques/algorithms to address
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