Research Engineer / Data Scientist

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.

• 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 

• 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

• 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