Researcher of Big Data, Data Science, and Scalabla Infrastructure

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経験内容

  • システム・ソフトウェア開発(インフラ系)
  • 研究開発

Eitan Frachtenberg is an experienced consultant, data scientist, and software developer. He has helped companies of all stages, from small startup to multi-billion dollar corporations answer deep data questions and scale their infrastructure to address their needs.he has worked with cutting edge analytics tools to compute extreme-scale problems efficiently and effectively. Some examples include:
- Data Scientist at Facebook, working on monetization analytics (billions of ad views per day). Before that, worked on Facebook''s high-efficiency data-center and server infrastructure (see below).
- Working with early-stage startups to bootstrap their data-science questions and data-driven infrastructure.
- Optimized semantic search engine at Powerset/Microsoft Bing.
Specialties:
- All aspects of computational scalability: hardware & infrastructure; middleware and operating systems; and application performance.
- Research experience in high-performance computing (HPC), systems, and computer architecture.
- big data analytics: statistics, visualization, machine learning.- Parallel and distributed programming.
- Performance optimization and tuning.
- Data Science and machine learning /deep learning algorithms.
Additional information on my hardware team leader role at Facebook:
One of his roles at Facebook's infrastructure organization was leading a team at Facebook Labs, which is responsible for evaluating nearly all future and current hardware solutions for deployment in our data structure. The role required working closely with the hardware vendors and the internal SW developers to evaluate both the technical aspects of each offering (performance on our workloads; power efficiency; tuning, etc. and TCO. Because of Facebook's scale, they also had to engage in forecasts of future supply and demand for these components. The components he primarily evaluated were CPUs (x86, ARM, and more exotic offerings) and networking (server-side). He also evaluated different storage so

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Computer scientist and software developer. Specialties: - Research experience in HPC, systems, and computer architecture. - big data analytics: statistics, visualization, machine learning. - Parallel and distributed programming. - Performance optimization and tuning. - Data Science and machine learning algorithms.