Working Student Data Science - Data Product

Descrizione

As a Data Science Working Student, you'll join our growing Data Products team and have a chance to make an enormous impact. The vast and diverse set of structured and unstructured data GetYourGuide has collected powering data products such as search, recommendations, SEM, or incentives. We have touch points across the business and aim to develop end-to-end solutions.

Team Mission 

The Growth Data Products team builds data products in partnership with our Paid Search and Customer Engagement teams. The team's prime focus is on fostering customer loyalty, developing pricing strategies, and optimizing the return on our whopping advertising budgets. Our algorithms help reach and engage millions of travelers throughout their journey to discover and book GetYourGuide's vast inventory. Our Data Scientists and MLOps Engineers work closely together to ship and operate data products. 

Responsibilities:

• Help us building data products that delight our customers and contribute to company success
• Contribute to projects from the business problem to the code in production, including ...
• … the analysis of vast amounts of data
• … the development and maintenance of data pipelines
• … the monitoring of your data products after deployment
• Contribute to our machine learning infrastructure and best practices
• Make your team more extraordinary via continuous improvements and knowledge sharing

Requirements:

• Machine Learning You apply regressors, classifiers, and recommenders. You understand in detail the underpinning of ML techniques. Experience in setting machine learning models into production is a plus.
• Software Engineering You are fluent in the Python programming language. Working  knowledge of distributed machine learning and computing framework (Spark) is a plus
• Analytics You can transform data into wisdom. You know how to test hypotheses. You are proficient with an analytics tool (pandas, R) and with SQL.
• Academic Background You are pursuing an advanced degree in a quantitative field and can quickly learn new skills or techniques.
• Experience You have university projects you want to share with us? You’ve done internships in the tech teams (product, engineering, design) of product-driven companies? Tell us about them!

Your Personal Touch: Do you contribute to an open source project? Do you participate in Kaggle competitions? Have you built your own project based on open data and just for fun? These are all things we would love to know about you!