Job type: Temps plein, CDI

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Position Snapshot

Location: Vers-chez-les-Blanc, Switzerland

Company: Nestlé Research, Scientific & Technical Operations
Act. Rate: Full-Time - 100%

Type of contact: Permanent contract

Genuine opportunities for career and personal development

Dynamic international working environment

Attractive additional benefits

Position Summary

Within Scientific IT and Data Office in the Scientific and Technical Operations (STO) Unit, we are looking for Data and Machine Learning Engineers who can enable Data Analysts and Data Scientists to accelerate data driven, purpose oriented scientific discoveries within Nestlé Research.

Nestlé Research is based in Lausanne, Switzerland and employs approximately 800 people. It consists of five research institutes: Health Sciences, Material Sciences, Food Safety & Analytical Sciences, Packaging Sciences and Agricultural Sciences. Nestlé Research combines fundamental science at the highest level, high-end analytical platforms leveraged by all research teams, and strong prototyping capabilities to accelerate the translation of science into innovation. Nestlé Research published around 1,000 scientific publications in peer review journals over the last five years, and files about 80 patents every year. Nestlé Research collaborates with approximately 100 universities or research institutes around the world. Learn more about Nestlé Research at www.Nestle.com/randd

As a Scientific Data & Machine Learning Engineer, you will be working on automating data pipeline management, building integrations between different scientific applications and in maintaining a cloud analytics platform as well as translating Machine Learning research into tangible applications to address needs of scientific discovery and product development

We offer a dynamic, inclusive, and international working environment with many opportunities across different companies, functions, and regions. Don’t miss the opportunity to join us and work with different teams in an agile and diverse context.

A Day in the Life of a Sr.Scientific Data & Machine Learning Engineer in Scientific IT and Data Office

  • Build & maintain automation of data flows
  • Build & maintain machine learning / advanced analytics applications
  • Study, research, prototype and validate machine learning applications
  • Documentation and maintenance of code
  • Partner with Data Scientists / Data Analytics Experts in addressing engineering challenges and ensuring scalability of prototyped applications
  • Expand and apply your knowledge about advances in data technology and machine learning

What will make you successful

  • Bachelor’s degree in Computer Science, Engineering, or related field.
  • 5+ years of experience in coding Life Sciences / Pharma / Food / Academia, applying agile development process.
  • Experience building, training, and optimizing neural networks
  • Experience in software development with Python.
  • Experience with Linux and Cloud Services, e.g. AWS or Microsoft Azure.
  • Experience on HTML, CSS, and JavaScript (Angular, React) for UI interactions.
  • Experience working with RESTful and JSON API structure.
  • Strong Relational database skills (SQL, DB connection)
  • Excellent communication skills – in English. Capable of explaining complex technical topics to non-technical audiences
  • Additional technical skills:
  • Experience with data visualization (Plotly, Matplotlib. etc.)
  • Knowledge of NO-SQL and Knowledge Graphs.
  • Machine learning (scipy, numpy, pandas)

We are Nestlé, the largest food and beverage company. We are 308,000 employees strong driven by the purpose of enhancing the quality of life and contributing to a healthier future. Our values are rooted in respect: respect for ourselves, respect for others, respect for diversity and respect for our future. With more than CHF 91.4 billion sales in 2018, we have an expansive presence with 413 factories in more than 85 countries. We believe our people are our most important asset, so we’ll offer you a dynamic inclusive international working environment with many opportunities across different businesses, functions and geographies, working with diverse teams and cultures. Want to learn more? Visit us at www.nestle.com.

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Deadline: 13-05-2024

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