Data Science Engineer

Data Science Engineer

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.

Many data science projects today struggle to be efficient and reproducible. 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 challenge to keep track of data versions; 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 collaborative platform developed by the SDSC to address these problems. Renku provides a knowledge infrastructure that seamlessly integrates interactive sessions (such as Jupyter, RStudio), automatic provenance tracking (which results were produced by whom and when), GitLab CI/CD, as well as version control systems for code, data and containerised environments. The key strength of Renku is its knowledge graph that captures the provenance of the analysis process by connecting versioned research objects, thus ensuring computational reproducibility. 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.

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,
• ensure knowledge transfer between stakeholders.
• 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/ ).

We offeryou 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 push forward the capabilities and performance of the team, 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.

• A Master's Degree (or higher preferred) in computer science or a related discipline (e.g. statistics, bioinformatics, physics, mathematics).
• 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 languages, in particular R and bash, 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.
• Familiarity with Semantic Web Technologies, such as RDF, SPARQL, OWL, SHACL, is desirable.
• 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 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.

We look forward to receiving your online application with the following documents:

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 Oksana Riba Grognuz; [email protected] (no applications).

For recruitment services the GTC of ETH Zurich apply.

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.