Research Engineer / Data Scientist

Description Research Engineering / Data Scientist Lancope’s Office of the CTO seeks an innovative Research Engineer / Data Scientist to develop new techniques in applying big data to network security. This is an exciting opportunity to join a growing team to invent and apply techniques in applied statistics, graph analysis, and machine learning toward telemetry analysis, data mining and threat detection. Main Responsibilities Conduct literature reviews and keep abreast of current techniques in applied statistics, machine learning, and big data Invent and/or apply new techniques to telemetry data to identify new security threats. Develop and document proofs-of-concept (POCs) to demonstrate the efficacy, performance, and scalability of new techniques Publish and present research findings, including methodology and measured efficacy improvements Partner with threat-research and engineering teams to turn successful POCs into product features and actionable intelligence Key Attributes Experience and desire to own innovative ideas from inventions, through proof-of-concept, to engineering and deployment Brings considerable experience, motivation and organization to make an impact on threat detection Intense curiosity to drive hands-on work to complete all phases of applied research We are looking for candidates that have: Experience in data manipulate using interpreted language (e.g. Python) and JVM language (e.g. Java or Scala) Extensive hands-on experience with Hadoop ecosystem. HBase and Spark highly desirable. Hands-on experience with distributed graph databases (e.g. Titan) Experience turning research ideas into actionable designs and POCs Comfortable working in an open, dynamic, applied-research team where multiple on-going projects and open collaboration are the norm Strong verbal, written, analytical, and persuasive skills. Able to communicate effectively with both technical and non-technical colleagues. Facility with applied statics or machine learning Experience in data mining and working with large, diverse, unfiltered data sets highly desirable. Advance degree in relevant field (PhD preferred) or commensurate direct experience