Job title: Machine Learning Engineer
Company: Danone
At Danone, we believe that every time we eat or drink, we vote for the world we want. As a leading food and beverage company, we make healthy, sustainably produced foods and beverages that nourish people's lives. As the largest Certified B Corporation in the world, we are committed to redefining success in business to ensure that through our brands we create real benefits for people, our communities, and the planet. In IT & Data, we inspire and empower Danone through the world of tech and data. Our mission is that, by 2025, technology and data are strategic differentiators of Danone, powered by an agile IT & Data organisation.
We are looking for a Machine Learning Engineer to join our team part-time for 6 months. The Global Data Science Team's mission is to develop new Data Science & AI tools to provide valuable insights to everybody at Danone, from Commercial to Operations. Danone is accelerating its data transformation, and we are strengthening our Data Science team by creating new positions around Europe. Your mission, as a ML Engineer, will be to deliver state-of-the-art, pragmatic, and creative data science solutions to answer complex business problems.
Our target is to work for all of Danone's businesses and address topics such as demand/supply forecasting, commodity pricing, milk collection optimization, marketing optimization, and environmental impact reduction. Data has no frontier; the team will be located in various European cities to be close to business partners we develop data science products for. This is a unique chance of being part of an international fellowship of data scientists & ML Engineers. Location for this position is Barcelona.
Key Accountabilities, Deliverables & KPIs:Apply state-of-the-art algorithms and predictive models (Machine Learning/Deep Learning) to answer business problems.Build data pipelines and industrialize algorithms.Support Data Scientists in the industrialization of models.Technical Skills Required:Programming: Python (pandas, numpy), Spark, Git.Modeling: supervised & unsupervised learning.Data Science tools/modules: Databricks / MLFlow.Experience in Data Science tools industrialization.Experience in data pipeline and industrialization is a plus.Monitor data input & model outcome.MLOps practices.Mandatory Skills:Ability to work with a variety of competencies, from business to Data Engineers.Qualifications:3 years of experience in Data Science / ML Engineering.A MSc, PhD or other Advanced Degree in a field linked to computer science, applied mathematics, statistics, machine learning, or closely related fields.Experience in industrializing ML tools.English is a must.
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