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- Aufgaben: Lead industry collaborations and turn machine learning skills into impactful projects.
- Arbeitgeber: Join EPFL, a top-ranked university in Europe, fostering innovation and research.
- Mitarbeitervorteile: Enjoy flexible hours, part-time options, and a healthy work-life balance.
- Warum dieser Job: Be part of a diverse team, learn from experts, and drive data science in Switzerland.
- Gewünschte Qualifikationen: Master's in Computer Science or related field; machine learning knowledge; bilingual in English and French.
- Andere Informationen: Contract starts on 01/05/2025; applications only via EPFL website.
Das voraussichtliche Gehalt liegt zwischen 43200 - 72000 € pro Jahr.
EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries.
Data Scientist – Innovation Collaborations
The Swiss Data Science Center (SDSC) is a strategic focus area of the ETH domain, with EPFL and ETH Zurich as founding partners, developing into a National Research Infrastructure in 2025. Its mission is to support academic labs, hospitals, industry and public sector stakeholders, including cantonal and federal administrations, through their entire data science journey, from the collection and management of data to machine learning, AI, and industrialization.
Your mission
You will work on one of the SDSC’s innovation partnerships in the French part of Switzerland. In this role, you will meet partners (companies) to understand their needs and help them define a high-impact project with the SDSC. You will be responsible for successfully carrying out the project thanks to your machine learning expertise with the help and support of the SDSC team.
Main duties and responsibilities include
- Be the main customer touchpoint of an industry collaboration
- Carry out projects with industry partners, from solution design to hands-on development
- Turn your machine learning skills into business value – go beyond split-fit-transform-test!
- Share expertise in data science and machine learning with fellow data scientists
- Presenting to a non-technical audience will also be part of your activities.
Your profile
The ideal candidate has:
- Master degree in Computer Science, Mathematics or similar fields
- Good knowledge of machine learning concepts
- Ability to present to technical and non-technical audiences
- Open to collaborative work and show team spirit
- Excellent communication skills in English and French
- Previous experience in companies or public sector organizations is appreciated but not mandatory
We offer
Do you see yourself helping Switzerland become more data-driven? Are you passionate about data science and with experience in machine learning? Are you keen to share what you know and get exposed to several projects in various industries? Are you eager to be part of a diverse and adaptable team with equal growth opportunities of its members at its core? If your answer to these questions is yes, you should consider joining us. Together, we can help move the Swiss Industry to the next level of data science. During your time at the Swiss Data Science Center, you will benefit from the following opportunities:
- Develop your soft skills and meet with key stakeholders in several industries
- Interact with and learn from fellow data scientists
- Discover new data science applications in various industries
- Exchange on advanced machine learning topics with our academic experts
We actively promote a healthy work-life balance in the workplace. Part-time arrangements and flexible hours can be explored based on individual circumstances. We are looking for candidates willing to contribute to an inclusive environment and eager to learn continuously.
Informations
Contract Start Date: 01/05/2025
Activity Rate: 100.00
Contract Type: CDD
Duration: 1 year, renewable
Reference: 1444
Contact
We look forward to receiving your online application including application letter, CV and diploma(s). Applications via email or postal services will not be considered. For further information about the Swiss Data Science Center please visit our website:
Only candidates who applied through EPFL website or our partner Jobup’s website will be considered.
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Data Scientist - Innovation Collaborations Arbeitgeber: École polytechnique fédérale de Lausanne, EPFL
Kontaktperson:
École polytechnique fédérale de Lausanne, EPFL HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Data Scientist - Innovation Collaborations
✨Tip Number 1
Familiarize yourself with the specific needs of industry partners in the French part of Switzerland. Research recent projects or collaborations that the Swiss Data Science Center has undertaken to understand their approach and how you can contribute.
✨Tip Number 2
Enhance your presentation skills, especially for non-technical audiences. Practice explaining complex machine learning concepts in simple terms, as this will be crucial when communicating with industry partners.
✨Tip Number 3
Network with current or former employees of the Swiss Data Science Center or similar organizations. Engaging with them can provide insights into the company culture and expectations, which can help you tailor your approach.
✨Tip Number 4
Showcase your collaborative spirit by participating in data science meetups or workshops. This not only builds your network but also demonstrates your commitment to teamwork and continuous learning, which are valued at EPFL.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Data Scientist - Innovation Collaborations
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure you fully understand the responsibilities and requirements of the Data Scientist position at EPFL. Familiarize yourself with the Swiss Data Science Center's mission and how your skills in machine learning can contribute to their projects.
Craft a Tailored Application Letter: Write a compelling application letter that highlights your relevant experience, particularly in machine learning and collaboration with industry partners. Emphasize your ability to communicate complex concepts to both technical and non-technical audiences.
Highlight Your Skills: In your CV, clearly outline your educational background, especially your Master’s degree in Computer Science or Mathematics. Include specific examples of your machine learning expertise and any previous collaborative projects you've worked on.
Follow Application Guidelines: Ensure you submit your application through the EPFL website or Jobup as specified. Include all required documents: your application letter, CV, and diplomas. Double-check for completeness and accuracy before hitting submit.
Wie du dich auf ein Vorstellungsgespräch bei École polytechnique fédérale de Lausanne, EPFL vorbereitest
✨Understand the Role and Responsibilities
Make sure you have a clear understanding of the Data Scientist - Innovation Collaborations role. Familiarize yourself with the main duties, such as being the main customer touchpoint and carrying out projects with industry partners. This will help you articulate how your skills align with their needs.
✨Showcase Your Machine Learning Expertise
Prepare to discuss your machine learning knowledge in detail. Be ready to provide examples of past projects where you've turned machine learning skills into business value. Highlight your ability to go beyond basic concepts and demonstrate practical applications.
✨Communicate Effectively with Diverse Audiences
Since you'll be presenting to both technical and non-technical audiences, practice explaining complex data science concepts in simple terms. This will showcase your communication skills and your ability to engage with various stakeholders.
✨Emphasize Collaboration and Team Spirit
The role requires open collaboration and teamwork. Share experiences where you've successfully worked in teams or contributed to group projects. Highlight your willingness to learn from others and adapt to different working styles.
