Data Science Engineer (m/f/d)

Zürich, Zurich, Switzerland

Full Time Entry-level / Junior
Bring! logo

Bring!

Die einfache Einkaufsliste ✓ immer dabei ✓ teilen mit Partner & Familie ✓ Über 10 Mio. Nutzer ▷ Vergiss’ den Papierzettel – Hol’ dir Bring! auf alle Geräte
Apply now Apply later


We build the perfect shopping companions

Our vision at Bring! Labs is to simplify daily shopping for people around the world. Our “Bring!” and “Profital” apps are used in millions of households to organize daily shopping, discover new delicious recipes and find the best local deals. We help our partners from FMCG and retail to reach out to their existing and future customers. We provide them with the most relevant advertising platform to showcase and promote their products at the right time: during the planning and execution of their household shopping.


Responsibilities

In this position, you will use various methods to transform raw data into useful data systems. For example, you’ll create algorithms and conduct statistical analysis. This role is possible for a 80-100% work pensum.

Your task includes the following:

  • Analyze and organize raw data
  • Build data systems and pipelines
  • Evaluate business needs and objectives
  • Interpret trends and patterns
  • Conduct complex data analysis and report on results

Requirements

We have high ambitions and the vision to change the way how users and customers plan and organize shopping. For this position we are looking for someone with substantial experience in Data Science or Engineering. You are the right fit if you have:

  • First experience in data engineering or a degree in Computer Science, IT, or similar field
  • Strong Software Engineering skills and technical expertise with machine learning, data mining, and data analytics
  • Knowledge of programming languages (e.g. Java and Scala)
  • Hands-on experience with SQL database design
  • Great numerical, analytical and statistical skills
  • If you have gained first experience with cloud platforms (e.g. AWS) and big data frameworks (Apache Spark / Apache Hadoop) this is a plus.
  • Business fluent in English, preferably German as well.

Benefits

You help to simplify shopping for millions around the world! At Bring! Labs we believe that talents can expand themself the best in a collaborative environment with an open and diverse work culture. We offer you a great place to work and where you can make an impact on millions.

  • Enjoy the flexibility of hybrid working: work from home or meet you great colleagues in on of our offices
  • attractive and modern working environment in the heart of Zürich, Basel or Berlin
  • You will enjoy a high degree of work freedom with flexible working hours
  • Feedback culture - we learn out of open communication !
  • Team spirit: just together we can reach for the stars!
  • many cool perks such as a free day off on your birthday, great barista coffee, latest high end hardware and much more...
  • We are in social events, BBQs, game nights, meetups in the Swiss Alps, or even stand-up paddle on Lake Zurich or Rhine swimming in Basel. Or what about a gaming session with Mario Kart? We got you covered!

Did you know, that Bring! Labs was named "No. 1 Online Startup" in Switzerland by the "Top 100 Startups" in 2020? Interested in more? Visit our career page!

We can’t wait to hear from you!

Please note that we ignore applications from headhunters, agencies or applicants who do not meet the language and location requirements.

Tags: AWS Big Data Data analysis Data Analytics Data Mining Engineering Hadoop Machine Learning Scala Spark SQL

Perks/benefits: Career development Flex hours Flex vacation Startup environment Team events

Region: Europe
Country: Switzerland
Job stats:  36  9  0
Category: Engineering Jobs
  • Share this job via
  • or

Other jobs like this

Explore more AI/ML/Data Science career opportunities

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.