In der aktuellen Covid-19 Situation laufen die Rekrutierungen weiter. Es kann dabei allerdings zu Verzögerungen kommen. Vielen Dank für Ihr Verständnis.

Data Science Engineer (W/M)

100%, Zurich, temporary

EPFL and ETH Zurich are seeking enthusiastic and experienced candidates with scientific IT expertise and a proven track record in and around data science and analytics on large-scale distributed platforms, services and applications, to staff up their national R&D Swiss Data Science Center. The ideal candidate will become part of the Swiss Data Science Center and will act as an enabler of data science activities within the research community from the ETH domains, Swiss universities, and the industry. In this role, you will liaise with data providers, data scientists, domain scientists, and industry partners; understand goals, gather requirements, implement solutions and ensure knowledge transfer between stakeholders.

Project background

About the Swiss Data Science Center (SDSC)

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 is 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 enables 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.

About Renku

Many data science projects today struggle to be efficient. It is difficult to identify available data, and then even more to share it; those who share data are often not recognized for their contribution; it is a struggle to keep track of versions of data; it is hard to see what code and data were used by whom to produce what results.  Renku  (https://datascience.ch/renku/https://renkulab.io/) is an open platform developed by SDSC to address these problems. Renku supports versioning of data and code; Renku tracks which results were produced by whom and when. Renku makes it possible to have greater trust in results and acknowledge the contributions of all those involved, regardless of whether their contribution was to implement the solution, provide the data, or ask the right questions.

Job description

  • Liaise with data providers, data scientists, domain scientists, and industry partners to gather requirements
  • Design, develop and set up novel (big) data science solutions into industrial and academic environments, using state of the art data science frameworks
  • Prepare tutorials, presentations, blogs, publications, about data science technologies
  • Provide trainings and promote the technology and services offered by the SDSC, in particular in connection with the Renku platform (https://renkulab.io/)

Your profile

  • A bachelor’s degree (MSc or higher preferred) in computer science or a related discipline (e.g., statistics, bioinformatics, physics, or electrical engineering)
  • A proven track record of crafting innovative and elegant software solutions, and a good command of the Python programming language. Familiarity with another programming/scripting language, especially R, is a strong plus.
  • Previous experience applying machine learning and (big) data analytics frameworks such as TensorFlow, Pytorch, Scikit-learn, Tidymodels, and the Apache Hadoop ecosystem, to real world problems.
  • Familiarity with software development best practices, such as agile software development and CI/CD, and tools like Git as well.
  • Consistent experience with the Linux operating system. Experience with cloud technology, and containers like Docker or Kubernetes, are highly desirable.
  • Ability to work well in a cross-functional environment and excel in communicating with your peers.
  • An interest to explore and learn novel technologies and put them to practice in uncharted territories.
  • Excellent command of the English language, both verbal and written (required). Good working knowledge of French or German, would be a plus.

ETH Zurich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.
Working, teaching and research at ETH Zurich Link icon

Interested?

We offer you a stimulating, startup-like, cross-disciplinary environment in a world-class research center that is part of two leading universities. In this dynamic position, you will make full use of your data science engineering and research skills and creativity to develop novel solutions for real cutting-edge questions. You will  design user interfaces, contribute to decision-making about the direction of the SDSC platforms and investigate available technology options. You will work in a data science setting alongside leading domain and computer science experts from the ETH domain as well as industry.  We have excellent ties to research groups worldwide, both academic and industrial.  You will get access to state-of-the-art infrastructure and resources.

We look forward to receiving your online application including a letter of motivation and a CV. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

For further information about the Swiss Data Science Center please visit our website www.datascience.ch. Questions regarding the position should be directed to Christine Choirat (christine.choirat@datascience.ch) (no applications).

Your workplace