Do you want to turn around the lives of people with skin issues by deploying your data science knowledge? And do you want to be part of revolutionizing an industry that desperately needs it? This Data Science job most likely comes with the highest impact on changing human beings' lives. The impact you will have on people's life can best be understood by watching the story from one of our users. Your knowledge will significantly contribute to providing our users with a happier life.

The opportunity and what we offer

• Be part of a user-first company where your decisions will impact our users directly
• A flat, transparent culture where everyone is encouraged to voice their opinions
• Flexible working hours and the possibility of working remotely
• Become co-owner of NØIE through warrants

Responsibilities

• Proactively lead our data infrastructure with full ownership and responsibility
• Build predictive models and machine learning algorithms
• Give input and direction on our data setup
• Analyze large amounts of information to discover trends and patterns

Qualifications

• Knowledge of probability statistics
• Knowledge of SQL and Python
• Experience with Python Libraries such as Pandas, Sklearn, Numpy
• Docker knowledge would be appreciated but not required

Data-driven dermatology

We utilize information from our users in adaptive bayesian statistical machine learning models that combine evidence-based knowledge and user feedback. Most importantly, the latter trains the models and increases their accuracy as we gather more feedback, making the products even better for the individual. Our community modelling approach makes NØIE unique and ultimately differentiates us from the conventional dermatological industry.

We have a strong focus on our data, and user feedback is the key in our approach. Currently, we have five people committed to working with our data. They focus on developing a continuously evolving model using AirFlow and Google BigQuery, but we know this can be improved, and we are looking into using Random Forest and other models.

If you have any questions, please contact Magnus Tuse Hansen at magnus@noie.com or +45 41826646.