Part-time Data Scientist | Ageras



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Copenhagen, Denmark

Position is open



We’re looking for a skilled and motivated Data Scientist, who is dedicated to interpret data, analyze results using statistical techniques to support Ageras in business decisions. As Europe's largest platform for professional services, we’re invested in adding transparency to the markets of accounting and legal services. Ageras is a disruptive, fast-paced company where IT is our core product.

As our Data Scientist, you’ll assist in creating key insight that will support in making strategic business decisions. You will be working in our passionate IT team, focusing on supplying crucial information and analytical data to help run and develop Ageras’ business.

Specifically, you will:

  • Develop and implement data analyses data collection systems
  • Create ongoing reports and dashboards
  • Build, train and deploy machine learning models and predictive algorithms
  • Present information using data visualization techniques
  • Gather and combine data from multiple data sources
  • Interpret trends and patterns in complex data sets
  • Communicate your findings to the management

You have a strong analytical mind-set and a clear flair for numbers and details. You are able to work independently, have a “can-do” attitude and thrive in a fast-paced business environment. Also, you’re curious, pro-active and a quick learner. Your critical thinking and problem-solving skills are essential for this role.

Maybe you’re studying for a Bachelor’s or Master’s degree in Data Science, Computer Science, or another relevant field and are eager to use your learning in practice. To us, it is important that you are ambitious, pay attention to detail and accuracy and are all about facts, figures and number crunching. We don’t expect you to have previous working experiences, but we expect that you are eager to develop yourself and learn quickly.

We think you may also be able to tick some of these boxes; if not we’ll help you get there:

  • Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information
  • An ability to draw conclusion from your analyses
  • An ability to translate your findings into an understandable document and present your findings
  • An understanding of machine learning and the tools that we use (Scikit-learn, pytorch, tensorflow)
  • Knowledge of SQL and R
  • Technical expertise regarding data models and data analysis
  • Problem solving aptitude

This is a part-time position of minimum 10 hours/week.

At Ageras, we take fun seriously, because motivated Agerians equal happy clients and partners. We go the extra mile to ensure that our employees come motivated and happy to work and thrive in our dynamic, international work environment. Our modern, open office space, in the heart of Copenhagen, creates an inspiring work atmosphere; we serve breakfast and lunch every day, drink very decent coffee and have fun Friday bars. Together we believe we can achieve great success and we are on a mission to conquer the world.

Now that we’ve caught your attention, it’s time for you to catch ours. Send us your English resume and a simple 1-page cover letter where you tell us why you are the right fit for us. If you have any work / portfolio you want to show us, please feel free to attach it too or send us a link. All applications are continuously evaluated, but you can expect to hear from us within 4 weeks.

If you have any questions regarding the position, please contact HR Consultant, Imke Wieboldt at +45 31 79 17 15.

About Ageras
At Ageras, we are all about making complex things simple, and that is because we believe it to be more fair, transparent, and empowering. We are building a simple ecosystem connecting clients to lawyers, accountants, and bookkeepers. We are an ambitious, young and fast-paced technology company in Copenhagen. After 6 years we are financially backed by one of the largest Private Equity funds, Investcorp, and have a footprint in Denmark, Sweden, Norway, the Netherlands, Germany, and the UK.

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