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22 May 2019

Full-timeData Scientist

Sqooba Deutschland GmbH – Posted by Sqooba.io Anywhere

Job Description

We are looking for Data Scientists on all experience levels in our Munich and Stuttgart office.

You are going to help our Data Science guild by:
- Being the hands on Data Scientist in a wide range of client projects
- Understanding data landscapes and how to unleash their potential
- Translating business problems and use cases into a data flow and algorithmic architecture
- Building Data Science solutions from PoC to full scale data applications
- Applying, improving and developing algorithms with a focus on results, scalability and
performance
- Building, maintaining and testing reusable modules to achieve high levels of flexibility and
confidence in production setups
- Continuously growing our repository of reusable code and tools
- Collaborating with Machine Learning Engineers, Developers and DevOps Engineers to make sure we re-define the benchmark in end2end Data (Science) applications every day
- Being in charge of the Data Science components throughout the entire lifecycle of a
solution, from deployment of the first slice to full production environment
- Learning about and gathering new Data Science approaches and the related tools ecosystem to introduce them to the rest of the Sqooba family

Our Data Science tools include:
- Python
- Pandas, Matplotlib or other visualization libraries
- Scikit-learn, Keras/Tensorflow, Spark MLlib, Spacy or other ML libraries
- Extensive usage of Git

Our stack is based on:
- Docker (Kubernetes)
- Spark (on Hadoop)
- Kafka
- Cassandra (or other NoSQL DBs)
- AWS and some of its services
- Azure and some of its services

We are mostly working as agile teams, you will need to use agile methodologies and tools.

About you (→ Personality and Behavior)
- Are passionate about data and algorithms
- Are hands on and prefer crunching data over producing PowerPoint slides
- Have the patience to listen to clients and translate their needs into a solution
- Want more than running a one-off analysis with some off-the-shelf application
- Get excited when you have to parallelize a problem and run it on a cluster because your laptop’s CPU really couldn’t handle it
- Happily admit knowledge gaps and mistakes, and openly share what you know
- Enjoy using and participating in the development of open source applications
- Enjoy working with cutting edge Data Science technology and applying the latest paradigms
- Are eager to be an early adopter of emerging big data applications
- Savor the challenges of getting a solution to work fully automated
- Team player and self-starter with a positive attitude

Your Background (→ Education and Experience)
- You would be a perfect fit if you have deep statistical and modeling knowledge paired with experience in developing Data Science solutions on premise and in the cloud
- If you have experience with big data platforms like Hadoop / Hortonworks / Cloudera it
would be a big plus
- You should know at least some parts of the stack described above, fluency in Python is a
must, and be willing to learn the rest. As we’re all hands on, you will be expected to be
quickly put on projects
- If you are familiar with the concept of developing solutions as micro services / deploying
them as containers, would be a plus
- Fluent English, German would be a nice plus

How to Apply

A step away from your best job ever. Every company will be a data company. Sqooba is a Swiss and German-based start-up, building analytical solutions and providing highly reliable end2end products for data streams and complex data landscapes. This is a hands-on position with a wide variety of roles and responsibilities, ranging from designing and building scalable Data Science solutions and cutting-edge algorithmic cores and helping companies to become much more data-driven. Join us at -> diver@sqooba.io or contact Norbert directly under norbert@sqooba.io

Job Categories: Development. Job Types: Full-time. Job Tags: #development, AI, aws, azure, data science, Docker, kafka, machine learning, and Spark. Salaries: Competitive.

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