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Senior Data Scientist (m/f) 80 - 100%

NZZ-Mediengruppe
Zürich, ZH

Jetzt bewerben

Details zur Stelle

Pensum: 80-100%
vor 7 Stunden

Leistungen

Zusätzliche Urlaubstage
Homeoffice-Möglichkeit

Qualifikationen

Englisch
Google Cloud Platform
Master
SQL
Recruiting
Kommunikationsfähigkeit
Python
Deutsch

Vollständige Stellenbeschreibung

The NZZ is one of the largest private media companies in Switzerland. We focus on high-quality, independent journalism and represent liberal perspectives. Our products offer our readers daily information and inspiration. In addition to our two main publications, “Neue Zürcher Zeitung” and “NZZ am Sonntag”, our portfolio includes various other titles, event series, podcasts, and TV formats.

Data Science is central to our mission of making data-driven decisions and developing innovative, data-based products. As an experienced Data Scientist, you have a proven track record of achieving business impact and optimizations through the use of data mining and machine learning techniques and will support our team starting 1st September 2026 or by agreement, as

Senior Data Scientist (m/f) 80 - 100%

Your tasks:

Developing and implementing new data products to support target group segmentation and optimize the commercial funnel and user journey
Taking responsibility for the entire model lifecycle – from ideation and experimentation to implementation and monitoring
Conducting exploratory data analyses to uncover trends, patterns, and valuable insights
Close, cross-functional collaboration with the Growth Tribe and the Marketing Team to translate business goals into data-driven solutions
Conduction complex analyses, including professional preparation and presentation of results
Promoting best practices in data science, especially regarding code quality, experimentation and reproducibility
Establishing and promoting modern standards in code quality, version control, reproducibility and agile project methods (e.g., Kanban/Scrum) within the data scenario

Your profile:

Master's degree in Mathematics, Statistics, Computer Science, or another quantitative field
At least 5 years of professional experience in data science, as well as sound theoretical and practical knowledge in statistics and machine learning (predictive and prescriptive)
Excellent understanding of experimental design, A/B testing, and data-driven decision-making
Experience with and understanding of the user journey and commercial funnels; experience with paywall and subscription models is desirable
Practical experience with the Google Cloud Platform (GCP), including Vertex AI
Excellent programming skills in Python and SQL
Good communication skills in English and German (at least level B) and the ability to collaborate effectively cross-functionally with technical and non-technical stakeholders
An entrepreneurial mindset and a strong "can-do" attitude, characterized by high initiative and a pragmatic, solution-oriented approach

We offer:

In this role, you will have a key position within the Growth Tribe (Technology organizational unit). You will independently and proactively ensure data-driven innovation as well as the lifecycle and quality management of our machine learning solutions and data products in coordination with the team.
Work Schedule: We support a healthy work-life balance with modern work models (flexible working hours within a 40-hour week (100%), partial work from home, birthday off, 5 weeks of vacation with the option to purchase additional vacation days, etc.).
Premium Working Environment: Our office is centrally located at Bellevue in the heart of Zurich – overlooking the opera house and the lake, and within walking distance of various shops and restaurants.

Your workplace

Your next step:

Are you interested? Then we look forward to receiving your online application.

Apply

Isabelle Liechti, HR Business Partner
+41 44 258 17 09

For this position, we admit only candidates who apply directly to us. Therefore applications from HR service providers will not be considered in the recruiting process. Thank you for your understanding.

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