What are the responsibilities and job description for the Research Engineer / Data Scientist position at Lancope?
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
