Håll muspekaren över eller tryck på en rad för fullständig statistik (EUR / månad i detta diagram).
Löneanalys
Löneerbjudandet i den här annonsen jämfört med referensen "Marknadsgenomsnitt: Medelnivå-nivå": mittpunkten ligger cirka 30 % under referensnivån. Samtidigt ligger erbjudandet fortfarande inom marknadsintervallet (€5 133–€11 459). Erbjudandets löneintervall (€5 000–€6 550) är smalare än marknaden, vilket tyder på mindre variation. Referensen bygger på 3 jämförbara annonser.
| \n\n---\n\n Marknad | Nedre gräns (25:e percentilen) | \n\n---\n\n Median | \n\n---\n\n Övre gräns (75:e percentilen) |
|---|---|---|---|
| Marknadssnitt: Data Scientist | €3 550/per månad | €5 954/per månad | €8 777/per månad |
| Lön i vår data — anges ej i annonsen (Medelnivå) | €5 000/per månad | €5 775/per månad | €6 550/per månad |
You will have impact and fun at work by: Developing predictive and statistical models that support large-scale User Acquisition decisions. Tackling challenging problems involving long-term forecasting, uncertainty quantification, optimization, and rare-event behaviour. Exploring and evaluating new modelling approaches and translating research ideas into production systems. Collaborating closely with stakeholders across Rovio — including UA managers, game teams, finance, analysts, engineers, and fellow data scientists — to solve high-impact business problems. Taking ownership of models throughout their lifecycle, from problem formulation and experimentation to deployment and monitoring. Contributing to a highly collaborative modelling culture where problems are scoped together, ideas are workshopped openly, and solutions are developed through pair coding, code reviews, and close day-to-day collaboration with the team.
Jobbdetaljer
Ansvarsområden
- Developing predictive and statistical models for user acquisition.
- Solving problems involving forecasting, uncertainty, optimization, and rare events.
- Exploring new modeling approaches and translating research into production.
- Collaborating with stakeholders to solve business problems.
- Owning models throughout their lifecycle.
- Contributing to a collaborative modeling culture.
Krav
- Extensive years of experience in data science.
- Academic degree in applied mathematics, statistics, machine learning, computer science, or related field.
- Proficiency in Python, including numerical and data science libraries, and designing data pipelines in cloud environments.
- Strong understanding of Bayesian modeling, Statistical inference, Predictive modeling, Optimization, Uncertainty quantification, Numerical methods.
- Ability to communicate complex technical concepts to both technical and non-technical teammates.
- Enjoyment of collaborative problem-solving.
Kompetenser & tekniker
Utbildningsnivå
Ingen utbildning krävs
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