Data Scientist (F/M) – Stockholm, Sweden
Infeurope is looking for a Data Scientist (F/M) based in Stockholm.
Tasks:
• Work closely with epidemiologists, disease experts and other client’s staff in developing and maintaining technical solutions for automated surveillance data analysis and visualisation;
• Strengthen existing surveillance data models, flows and routine outputs through state-of the art technology, optimising integration, automation and user-friendliness while complying with scientific standards and best practice;
• Identify, assess, validate, and support data linkage with, external large databases to enhance routine surveillance, help to answer specific public health questions and support public health decision-making;
• Create, maintain and refine automated surveillance processes and outputs including surveillance and situational awareness dashboards in the context of early threat detection, assessment and response planning;
• Support relevant IT projects by ensuring that data requirements are properly defined;
• Any other tasks related to his/her area of work as requested.
Minimum requirements:
• University degree with at least 3 years of experience in data science OR non-university degree with at least 5 years of experience in data science;
• At least three years of experience during the past five years in :
– Evaluating and optimising large complex data sets and existing outputs;
– Data quality assurance;
– Automating data flows and output production;
– Data linkage;
– Advanced R, in particular creating outputs and dashboards using Markdown and Shiny;
– Python;
• Level of English, both written and spoken corresponding to CEFR level equal to B2 or higher.
Advantageous experience (at least 6 months during the past five years):
• R version control (git) and containerisation (Docker);
• Data science applied to infectious diseases, epidemiology, surveillance or public health;
• Python libraries such as Pandas, NumPy, Matplotlib, Plotly, Statmodels, SciPy;
• Exploiting e-health data;
• Work in a multicultural context.