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Data Scientist @ Studentpulse

StudentPulse is an intelligent student check-in platform for student engagement and support in higher education. If needed, students can request help or we can nudge them to take appropriate action. Currently, we are helping 50+ universities around Europe elevate students to new heights of personal, social, and academic well-being 🫂

The role

As our new Data scientist you will design, develop and implement concrete machine learning models for various use cases for education industry. You will keep abreast of the latest advancements in the field of AI, machine learning, and data science and integrate relevant new learnings and technologies into our work.

The role is remote based with an option to work from Aalborg HQ in Denmark. If you choose to work remotely, we expect to see you in person every ~2 months.

Start date - ASAP.

By playing an active role you will be responsible of setting and documenting standards and best practices for data science in StudentPulse.

Your primary tasks will be to:

  • Work closely with cross-functional teams, including data scientists, developers and business stakeholders, to ensure the successful deployment and scaling of data products.
  • Apply statistical analysis and machine learning techniques to derive valuable insights from large volumes of historical and current industrial data.
  • Interpret complex data sets and communicate results clearly to technical and non-technical team members.
  • Lead in the development of data collection strategies to optimize statistical efficiency and data quality.
  • Work with stakeholders throughout the organization to identify opportunities and use cases for leveraging company data to drive business results.

Your Qualifications

To succeed in this role, you need to be curious and self-driven, with the ability to approach problems in a creative manner. You have a strong personal drive to get the job done on time without compromising on the quality of your deliverables.You are naturally curious about new data trends and detail-oriented with the ability to prioritise important data and tasks.

Moreover, we expect that you:

  • Have a work experience in data science and/or machine learning operations.
  • Are high proficiency in programming languages such as Python, R or SQL.
  • Experienced working with cloud solutions (We use AWS).
  • Are a strong communicator with a high level of personal integrity and taking responsibility for driving your own work while at the same time work within the team.
  • Have excellent communication skills and are fluent in written and spoken English.

Your background

In a (well-established) startup, one of the key points for success is to have the right dynamic and the right drive in the team. We have each others’ back, and we have fun when we are at work - both with coworkers and with our customers.

With that said: You do not have to be able to say yes to every point on the following list, but the more the merrier:

  • Devoted: It hurts you when it hurts the customers
  • Proactive: You do not just sit and wait for improvement, you actively take initiative and improve it
  • Caring: You have an interest in your fellow students, perhaps as a member of the student council
  • Brave: You do not hesitate and take ownership of your work

If you believe you have what it takes to excel as a data scientist at StudentPulse or have additional questions and want to have a chat, we’d love to hear from you 😊

Workplace

Nyhavnsgade 14, 9000 Aalborg

Position

Data Scientist

Application deadline

As soon as possible

Start date

As soon as possible

Created

01.10.2023

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Contact person

Gintaras Arstikaitis

Head of Technology

Phone 37068462241 / ga@companyoung.com

Company description

StudentPulse is an international start-up (2021) owned by CompanYoung Group.

We are currently a team of ten dedicated employees, sharing office with our 70 colleagues from CompanYoung.

All we care about is building an intelligent platform that helps educational institutions to increase student satisfaction through data, globally.