Senior Statistical Data Scientist - Remote Analytics

HumanI; Genf; Vor Ort; CHF 110.000 - 150.000; Vollzeit

Zusammenfassung

HumanI seeks a Statistical Data Scientist to transform complex biological data into actionable insights, using rigorous statistics and modern methodologies. You will work with engineers, biologists, and data teams across time zones to enable evidence-based decisions.

Responsibilities include designing experiments, building predictive models for breeding and product development, and applying machine learning where it adds value, while ensuring robustness and reproducibility of results.

Qualifikationen

• MSc or PhD in Statistics, Biostatistics, Applied Mathematics, Quantitative Genetics, Econometrics, or related field.
• Strong grounding in statistical inference, experimental design, regression, and mixed models.
• Experience with Python and/or R; familiarity with predictive modelling and ML approaches.

Aufgaben

• Collaborate with seed engineers, breeders, biologists, and data engineers.
• Translate complex statistical results into clear, decision-ready insights.
• Design and analyse biological and experimental datasets with statistical rigour.
• Build predictive models for breeding and product development decisions.
• Apply machine learning where it adds meaningful value beyond classical statistics.
• Ensure experimental conclusions are robust, reproducible, and well-validated.

Kenntnisse

Statistical inference

Experimental design

Regression analysis

Mixed models

Python

R

Predictive modelling

Machine learning

Communication skills

Scientific problem solving

Ausbildung

MSc or PhD in Statistics / Biostatistics / Applied Mathematics / Quantitative Genetics / Econometrics

Tools

Python

R

Jobbeschreibung

HumanI seeks a Statistical Data Scientist to transform complex biological data into actionable insights, using rigorous statistics and modern methodologies. You will work with engineers, biologists, and data teams across time zones to enable evidence-based decisions.

Responsibilities include designing experiments, building predictive models for breeding and product development, and applying machine learning where it adds value, while ensuring robustness and reproducibility of results.