below marketmost similar roles pay hereabove market
This role pays more than
65%
of similar roles. Most pay
$135,000–$205,875
— the blue band above.
At the midpoint, this role pays about
$180k
versus about
$170k
for comparable roles.
Based on 240 similar postings.
Employer
About Novartis
Novartis is a global biopharmaceutical company that researches, develops, manufactures, and markets prescription drugs in areas including oncology, immunology, neuroscience, and cardiology. Industry: Biopharmaceuticals
Novartis currently has
17 open roles
on FindRole.
Listed pay typically runs
$176,400–$327,600
across 17 roles with salary data.
The Senior Expert Data Scientist, Human Genetics joins the Cardiovascular and Metabolic Disease research organization to support therapeutic target discovery and patient selection strategies. Working within the Biomedical Research team, you will analyze whole exome and genome sequencing data to identify genetic variants, genes, and biological pathways associated with cardiovascular and metabolic diseases. You will develop statistical genetics and bioinformatics methods for variant annotation, association analysis, burden testing, and causal inference. The role requires integrating human genetics with transcriptomic, proteomic, and functional genomics data to develop disease insights. Key technical requirements include proficiency in Python, R, and Linux environments, along with experience in workflow management systems like Git. You will use these tools to derive biologically meaningful conclusions for innovative drug discovery and precision medicine programs.
Analyze and interpret whole exome and genome sequencing data to identify genetic variants and biological pathways.
Develop statistical genetics and bioinformatics methods for variant annotation, burden testing, and causal inference.
Identify and validate novel therapeutic targets using human genetic evidence and complementary genomic data.
Develop patient selection and stratification strategies to identify genetically defined subgroups for clinical programs.
Integrate human genetics results with transcriptomic, proteomic, and functional genomics data to derive disease insights.
Build reproducible, well-documented analytical workflows for large-scale genomic data analysis.
Communicate scientific findings through presentations, written reports, and manuscripts for cross-functional project teams.
What we're looking for
PhD with 2-3+ years or MS with 6+ years of industry experience in human genetics, statistical genetics, computational biology, bioinformatics, epidemiology, biostatistics, or a related field.
Postdoctoral research experience (preferred).
Demonstrated experience analyzing whole exome/genome sequencing data, including variant quality control, annotation, filtering, association testing, and interpretation.
Strong understanding of human genetics and statistical genetics principles, including rare-variant analysis and genotype-phenotype associations.
Familiarity with genome-wide association studies, phenome-wide association studies, polygenic risk scores, Mendelian randomization, or functional genomics.
Experience integrating genomic data with clinical, molecular, or multi-omic datasets.
Programming and data analysis expertise in Python or R, along with proficiency in Linux or Unix-based computing environments.
Knowledge of workflow management systems (Git), collaborative coding, and reproducible research practices.
Machine Learning
Python
R
Deep Learning
Mechanistic Modelling
PK/PD
QSP
PyTorch
Keras
scikit-learn
Pandas
SQL
Data Science
Statistics
Data Visualization
Exploratory Data Analysis
Version Control
NLP
GenAI