Data Scientist

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Data Scientist

At Starred we're looking for a Data Scientist to join our team.

Full-time · Amsterdam

About the job

Are you as an experienced Data Scientist ready for the next step in your career? Starred offers you this opportunity! We are looking for a Data Scientist who is comfortable developing machine learning models ready for production. Someone who can lead our data science projects from the ideation phase into implementation and deployment whilst having one goal in mind, making the impact that our clients expect from working with Starred.

We build and deliver data driven solutions using technologies like Apache PySpark, Serverless applications and/or cloud-native components (AWS). Join our team R&D team working on various projects and discovering patterns in big and complex data sets. Help us build custom-made, state-of-the-art, data solutions for our clients, and bring new insight into production.

Starred's challenge

The Starred platform contains a wealth of data that needs to be analysed and turned into actionable insights. Our clients rely on our data in their decision making processes to improve their candidates’ and/or employees’ lives. This requires the highest level of data integrity, security, and efficiency. It also challenges the way data are analysed, and visualised. We’re constantly challenged by our customers to provide them the right insights to enable them to stay ahead of the competition regarding their recruitment goals, or their people goals as an employer.

About you

  • A minimum of 5 years experience in a position as data scientist, machine learning engineer, or similar

  • You’re able to communicate about data analysis on different levels: with your development co-workers, and also with our customer contacts providing them with the insights they need.

  • You follow the latest Data Science developments, and are excited about learning new technology.

  • Experience in using visualisation tools (BI) and packages (ggplot)

  • Experience in working with AWS cloud environment

  • Have a good knowledge of Natural Language processing, Sentiment Analysis and Text mining

  • Experience with containerisation in Docker

  • Experience in making ML production pipeline in cloud environment

  • Advanced experience with Machine Learning (deep knowledge about supervised and unsupervised learning and techniques and tools)

  • Advanced experience in Python and R (expert in using Pandas, Numpy)

  • Advanced knowledge of statistics and mathematics (hypothesis testing, correlation test)

  • Master in Computer Science, Artificial Intelligence, Econometrics or similar

Cultural fit

Start with the human: No matter how advanced technology becomes, the cooperation between people should remain at the core. The personal relationships we maintain with our customers are crucial to the success of Starred.

Embrace & drive change: Don’t accept something because it is like it is. Break through the status quo, innovate and reinvent your job and yourself constantly. In other words: embrace change.

Take ownership: Take responsibility for your work, your customers, your colleagues… your mistakes. In other words: at Starred you don’t ‘rent’ your job, you ‘own’ your job.

Work smarter: Sometimes there’s an alternative to working harder: working smarter. Which tools could you deploy? Who could help you out? Which partnership could speed you up? We’re constantly looking for ways in which we can work smarter.

Building together: Finally, you’re not alone. Without marketing there would be no leads, without the development team there would be no product, without customer happiness there would be no happy customers, and without sales there would be no new customers. We’re building Starred together.

Apply for the job

Things to keep in mind when applying:

We care more about the why rather than just the result;

Our initial review is mostly based on your answers to the questions we have in the application form and your motivation to contact us.

Understanding what we do will make our interviews a lot more productive and efficient, make sure to do research beforehand.