Remote Senior Data Scientist - Life Sciences Research

Placements24; Queenstown; Hybrid; NZD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Dental & vision insurance

Flexible remote work with home office

Generous paid time off & professional 

Development opportunities

Job summary

Placements24 is seeking a highly skilled Senior Data Scientist to join a fully remote, cutting-edge life sciences research division. Leverage advanced analytics and ML to extract insights from complex biological and clinical datasets, driving data-driven decisions across multiple programs.

Responsibilities include developing models, statistical analyses, data extraction and cleaning, collaboration with biologists and clinicians, data visualization, and staying current with ML advances.

Qualifications

• Masters or PhD in a quantitative field such as Data Science, Statistics, Computer Science, Bioinformatics or related.
• Minimum 6 years of professional Data Scientist experience in life sciences.

Responsibilities

• Develop, implement, and validate predictive models for large-scale biological and clinical datasets.
• Design and execute statistical analyses, hypothesis testing, and experimental design for research projects.
• Extract, clean, and transform complex data from various sources, ensuring data integrity and quality.
• Collaborate with biologists, chemists, and clinicians to translate research questions into data science problems.
• Visualize data and model outputs for presentations to technical and non-technical audiences.
• Stay current with advances in data science and life sciences domains.

Skills

Python

R

Pandas

Scikit-learn

TensorFlow

Statistical modeling

Hypothesis testing

Experiment design

Communication

Education

Master's or PhD in Data Science/Statistics/CS/Bioinformatics

Tools

AWS

Azure

GCP

Job description

Placements24 is seeking a highly skilled Senior Data Scientist to join a fully remote, cutting-edge life sciences research division. Leverage advanced analytics and ML to extract insights from complex biological and clinical datasets, driving data-driven decisions across multiple programs.

Responsibilities include developing models, statistical analyses, data extraction and cleaning, collaboration with biologists and clinicians, data visualization, and staying current with ML advances.