Data Scientist / Data Scientistess

ETH Zürich - June 29, 2025

Swiss Data Science Center (SDSC)

The Swiss Data Science Center (SDSC) has been a National Research Infrastructure since 2025, evolving from a strategic focus area of the ETH domain, with EPFL and ETH Zurich as founding partners. Our mandate is to support academic groups, research, hospitals, industry, and the public sector at large, including cantonal and federal administrations. The center accompanies and supports their entire data science journey—from data collection and management to machine learning, AI, and industrialization.

Our multidisciplinary team of data scientists and experts spans several domains and operates from offices located in Zurich, Lausanne, and Villigen.

Join Our Innovation Team

We are currently seeking a talented Data Scientist to join the SDSC's Innovation team, dedicated to accelerating the adoption of data science among Swiss companies, public sector organizations, and NGOs.

If you are passionate about data science, familiar with machine learning, and eager to deepen your expertise, we want to hear from you. Are you ready to tackle industry and public sector challenges while being mentored by seasoned data scientists? Do you thrive in a diverse, adaptable team focused on personal and professional growth? If so, consider joining our dynamic team of dedicated data scientists who take pride in solving business challenges and delivering actionable insights.

Responsibilities

  • Design, implement, and test machine learning systems to address challenges faced by industry and the public sector.
  • Engage in all aspects of a data science research project, from understanding business needs to developing proofs of concept and communicating results.
  • Specifically, in this role, you will:
    • Meet with customers to understand their business requirements and design targeted data science solutions.
    • Code and test proposed solutions (PoC), communicate results to stakeholders, and provide comprehensive reports on progress and outcomes.
    • Occasionally present data science findings to non-technical audiences.

Candidate Profile

We are looking for candidates (m/w/d) with the following qualifications:

  • Master’s degree in Computer Science, Mathematics, Physics, or a related field (PhD is a plus).
  • Ability to effectively present results to varied audiences (both technical and non-technical).
  • Solid understanding of machine learning concepts along with programming skills in Python, R, or similar languages.
  • 1-3 years of data science experience in the industry.
  • Fluency in (Swiss) German and English.
  • Willingness to collaborate, eagerness to learn new concepts and methods, and a commitment to fostering an inclusive environment.
  • Knowledge in NLP, Computer Vision, and Deep Learning is a plus.

Working Environment

In this role, you will have the opportunity to be mentored by experienced data scientists with academic backgrounds alongside industry and public sector experts. You will also collaborate with system specialists on data engineering aspects, and benefit from a training-oriented academic environment to enhance your skills in machine learning and statistics.

Duration and Start Date

Start date: September 2025 or by agreement

Duration: 1-year renewable

Application Process

We look forward to receiving your online application using the form below, which should include the following documents:

  • Cover letter
  • CV
  • Diploma(s)

Please note that only applications matching the job profile will be considered. For further information about the Swiss Data Science Center (SDSC), please visit our website. Queries regarding the position can be directed to Anna Fournier at anna.fournier@sdsc.ethz.ch or Saurabh Bhargava at saurabh.bhargava@sdsc.ethz.ch (no applications).

For recruitment services, the General Terms and Conditions (GTC) of ETH Zurich apply.

Location : Zürich ETH-Zentrum
Country : Switzerland

Application Form

Please enter your information in the following form and attach your resume (CV)

Only pdf, Word, or OpenOffice file. Maximum file size: 3 MB.