Senior Data Scientist

     
AnbieterEidgenössische Technische Hochschule Lausanne, EPFL
Erschienen
ArbeitsortLausanne, Genfersee Region, Schweiz
KategorieInformatik / Telekom
Mathematik
FunktionFeste Anstellung / Mitarbeiter

Beschreibung

33195

Description

EPFL and ETH Zurich are seeking enthusiastic and experienced candidates with a proven track record in machine learning, statistics or data mining applied to large-scale real-world problems to staff up their upcoming national R&D center for data science.

In this role, you will apply your practical experience in mining, cleansing, and analyzing messy data, your deep understanding of data science algorithms, and your willingness to write code to explore problems and understand data, all while solving challenging real-world problems at large scale. You will work hand-in-hand with experts (academics and from the private sector) in domains ranging from personalized health and personalized medicine, Smart / Future cities - in particular transportation and energy - earth and environmental science, smart manufacturing, computational social science and economics, and digital humanities.

Specifically, you will:
  • Liaise with experts in select domains to gather requirements and translate them into well-posed data science problems
  • Mine data from a variety of sources, both stored historical data and streaming data
  • Develop statistical methods and models using a variety of tools and programming languages
  • Design experiments for quantitative and qualitative assessment of different algorithms
  • Deploy data processing and analysis pipelines on the center’s Insights-as-a-Service platform
  • Work hand-in-hand with the engineering department to help incubate replicable analytics methods into the center’s platform

Candidates are expected to possess deep hands-on experience in solving complex real-world problems using data-driven methods. The ideal candidate also has a good background in Big Data technologies (e.g. Hadoop, Spark), and with building applications at scale.

Requirements

You:
  • Have a MSc in Computer Science, Mathematics, Electrical Engineering or related disciplines. Ph.D. degree is a strong plus
  • Have deep knowledge in data mining, machine learning, natural language processing, or information retrieval. A subject matter expertise in an industrial domain is highly appreciated.
  • Have enough experience and programming knowledge to clean and scrub noisy datasets
  • Have the ability to create complex prototypes in R, Python, or Scala. Ideally you have experience with Map Reduce technology using Spark, MLlib, Mahout or similar.
  • Seek out opportunities to contribute to the open source community
  • Work well in a cross-functional environment and excel in communicating with your peers
  • Have excellent command of the English language, both verbal and written. Good working knowledge of French or German is highly desirable.

Benefits

  • A stimulating, startup-like, cross-disciplinary environment in a leading university
  • Opportunities for turning academic research into impactful solutions
  • Excellent ties to research groups worldwide, both academic and industrial
  • Access to state-of-the-art infrastructure and resources

About Us

The Swiss Data Science Center (SDSC, datascience.ch ) is a national center between EPFL and ETH Zurich, whose mission is to accelerate the use of data science and machine learning techniques broadly within academic disciplines of the ETH Domain and the Swiss academic community at large. It aims to federate data providers, data and computer scientists, and subject-matter experts around a cutting-edge analytics platform offering domain-specific “Insights-as-a-Service” while addressing security and privacy issues inherent to the field of data science. The SDSC will be composed of a large multi-disciplinary team of data & computer scientists and experts in relevant domains, distributed between our offices in Lausanne and Zurich. The unique synergy that the center will enable among the institutions of the ETH Domain and between academic and industrial stakeholders in both data science and across carefully selected domains is expected to foster scientific breakthroughs with significant societal impact.

Activity rate: Full-time or part-time

Start date: December 1, 2016, or to be discussed

Procedure for applications:

Candidates should submit their application online at

Contact:

For further information, please contact Dr. Olivier Verscheure (olivier.verscheure [at] epfl[.]ch)

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