Security Data Scientist

Obsidian is seeking expert researchers to tackle a variety of problems that impact the bleeding edge of machine learning and artificial intelligence, with a focus on applications in computer security. We’re developing a team by drawing from the research fields in statistics, computer science, mathematics and related fields to help us achieve these goals.

At Obsidian, our research team is at the core of our business. You will be part of a highly visible, agile team working on critical problems that directly affect the company’s success. Our researchers regularly appear at various global conferences and are some of the most sought-after thought leaders in the security industry. As part of the research group, you will leverage your problem-solving and analytical skills to further our capabilities, as well as publish and present new and novel research.

Specifically, you’re someone who will:
  •  Wants to build and develop intellectual property through the research and implementation of new approaches in machine learning
  • Approaches problems from an adversarial mindset in an effort to circumvent prediction systems
  • Works with internal product and engineering teams to drive development of new products
  • Has the capability to translate and implement newly published research on specific datasets and problems to validate approaches and potentially improve
  • Is experienced wrangling large volumes of data and applying machine learning techniques towards real product and business problems
  • Invests time in research including publications, and is committed to keeping up with AI trends
  • Develop working prototypes of algorithms and evaluate and compare metrics based on large, real-world data sets

Qualifications:
  • Enjoys the startup life and is willing to live/relocate to balmy Southern California
  • MS or Ph.D. in computer science, statistics, or applied math
  • 2+ years of experience applying statistical/ML algorithms and techniques to real-world data sets
  • Expert knowledge of a scientific computing language such as R, Matlab or Python
  • Familiarity with Apache Spark
  • Designs scalable processes to collect, manipulate, present, and analyze large datasets in a production-ready environment
  • Experience with large volumes of data, algorithms, and prototyping
  • Strong written and oral skills (in English)


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