Data Scientist - Genomics

Placements24; Canterbury; On-site; NZD 90,000 - 140,000; Full time

Benefits offered by this job

Competitive salary

Health insurance

Professional development

Collaborative culture

State-of-the-art facilities

Retirement plan

Job summary

Placements24 is seeking a skilled Data Scientist with a Genomics focus to join our research team in Welkom. You will analyze large genomic datasets and build models for disease insights.

You will work with geneticists and clinicians, design workflows, ensure reproducibility, and communicate findings to stakeholders. On-site environment with modern facilities.

Qualifications

• Master's or Ph.D. degree in Data Science, Bioinformatics, Statistics, Computer Science, or a related field.
• Proven experience in analyzing genomic data using statistical and machine learning techniques.
• Proficiency in programming languages such as Python or R, and familiarity with relevant bioinformatics libraries.
• Experience with common genomic data formats and analysis tools.
• Strong understanding of population genetics, variant calling, and gene expression analysis.

Responsibilities

• Analyze large-scale genomic datasets (e.g., WGS, WES, RNA-Seq) to identify genetic variations and functional associations.
• Develop and implement machine learning models for disease prediction and patient stratification.
• Collaborate with geneticists and clinicians to interpret findings and translate them into actionable biological insights.
• Design and execute data analysis workflows, ensuring data integrity and reproducibility.
• Visualize complex genomic data for effective communication to both technical and non-technical stakeholders.
• Stay abreast of the latest advancements in genomics and data science methodologies.

Skills

Genomic data analysis

Statistical methods

Machine learning

Python

R

Bioinformatics

Education

Master's or PhD in related field

Tools

Python

R

Genomics tools

Job description

About the Role

Our client is looking for a skilled Data Scientist with a strong background in Genomics to join their dedicated research team based in Welkom . This role is integral to unlocking insights from vast genomic datasets, driving forward new discoveries in personalized medicine and disease research. You will work hands‑on with cutting‑edge technologies, applying advanced analytical techniques to complex biological information. This is a fantastic opportunity for an analytical mind to contribute significantly to impactful scientific projects within a collaborative, on‑site environment that encourages innovation and rigorous scientific inquiry.

Key Responsibilities

• Analyze large-scale genomic datasets (e.g., WGS, WES, RNA-Seq) to identify genetic variations and functional associations.
• Develop and implement machine learning models for disease prediction and patient stratification.
• Collaborate with geneticists and clinicians to interpret findings and translate them into actionable biological insights.
• Design and execute data analysis workflows, ensuring data integrity and reproducibility.
• Visualize complex genomic data for effective communication to both technical and non-technical stakeholders.
• Stay abreast of the latest advancements in genomics and data science methodologies.

Requirements

• Master's or Ph.D. degree in Data Science, Bioinformatics, Statistics, Computer Science, or a related field.
• Proven experience in analyzing genomic data using statistical and machine learning techniques.
• Proficiency in programming languages such as Python or R, and familiarity with relevant bioinformatics libraries.
• Experience with common genomic data formats and analysis tools.
• Strong understanding of population genetics, variant calling, and gene expression analysis.
• Excellent problem-solving skills and the ability to work collaboratively within a team environment in Welkom.

Benefits

• Competitive salary and performance-based incentives.
• Comprehensive health, dental, and vision insurance plans.
• Opportunities for continuous learning and professional development.
• Collaborative and supportive work culture focused on scientific advancement.
• State-of-the-art laboratory and computational facilities.
• Defined contribution retirement plan.