Senior Expert Data Scientist, Human Genetics

Novartis (Internal Careers for Acquired Entities)

Cambridge (MA)

On-site

USD 126,000 - 234,000

Full time

4 days ago
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Job summary

Novartis is seeking a highly skilled computational scientist to join the CVM research team in Cambridge, MA. The role focuses on applying human genetics and genomic data science to target discovery and patient stratification for cardiovascular and metabolic diseases.

You will work with geneticists, computational biologists, and clinical teams to translate genetic insights into actionable drug discovery strategies, while developing robust analytic workflows and communicating results effectively.

Qualifications

  • PhD or equivalent in genetics, genomics, bioinformatics, or related field.
  • Experience analyzing whole exome/genome sequencing data and variants.
  • Strong foundation in statistical genetics and data interpretation.

Responsibilities

  • Analyze whole exome/genome sequencing data to identify variants and pathways.
  • Develop statistical genetics methods for variant annotation and association tests.
  • Support identification and validation of novel therapeutic targets using genetic evidence.
  • Contribute to patient stratification and genetically defined subgroups.
  • Integrate genetics results with multi-omic data to inform insights.
  • Collaborate with cross-functional teams to translate findings into recommendations.
  • Develop reproducible analytical workflows and best-practice documentation.
  • Present results in presentations, reports, and manuscripts.

Skills

Python
R Programming
Statistical Analysis
Machine Learning
SQL

Education

PhD in genetics/genomics
Postdoctoral experience preferred

Tools

Git
Linux/Unix
Genomic data analysis tools

Job description

Band

Level 4


Job Description Summary

Location: Cambridge


This position is located in Cambridge, MA and does not have the ability to be located remotely. Please only apply if this area is accessible to you. We are seeking a highly motivated computational scientist to join the Cardiovascular and Metabolic Disease (CVM) research organization at Biomedical Research (BR) in Cambridge, MA. In this role, you will apply human genetics, statistical genetics, and genomic data science to support new therapeutic target discovery and patient selection strategies across CVM diseases. The successful candidate will work closely with geneticists, computational biologists, disease-area scientists, translational researchers, and clinical development colleagues to generate actionable insights from human genetic and genomic data. This is an opportunity to contribute to innovative drug discovery programs and help advance genetically informed approaches to precision medicine.


Job Description

Key Responsibilities


  • Analyze and interpret whole exome/genome sequencing data to identify genetic variants, genes, and biological pathways associated with cardiovascular and metabolic diseases.

  • Develop and apply statistical genetics and bioinformatics methods for variant annotation, association analysis, burden testing, rare-variant analysis, causal inference, and gene prioritization.

  • Support the identification, evaluation, and validation of novel therapeutic targets using human genetic evidence and complementary genomic data sources.

  • Contribute to patient selection and stratification strategies for research and clinical programs, including the identification of genetically defined patient subgroups.

  • Integrate human genetics results with transcriptomic, proteomic, functional genomics, clinical, and other relevant data to develop disease and target insights.

  • Collaborate with cross-functional project teams to define analytical strategies, interpret findings, and translate results into clear scientific recommendations.

  • Develop reproducible, well-documented analytical workflows and contribute to best practices for genomic data analysis.

  • Communicate results through presentations, written reports, scientific manuscripts, and internal project updates.

  • Stay current with advances in human genetics, statistical genetics, genomic medicine, and computational methods relevant to drug discovery and development.


Essential Requirements


  • 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 is 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.

  • Ability to work with large-scale genomic datasets and use appropriate statistical and computational methods to derive biologically meaningful conclusions.

  • Strong scientific communication, collaboration, and problem-solving skills.


Preferred Qualifications


  • Experience applying human genetic evidence to target discovery, target validation, or drug development.


Novartis Compensation and Benefit Summary:

The salary for this position is expected to range between $126,000 and $234,000 per year.


The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.


Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.


US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.


EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.


Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an e-mail to tas.nacomms@novartis.com call +1 (877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message. https://www.novartis.com/careers/careers-research/notice-all-applicants-us-job-openings


Salary Range

$126,000.00 - $234,000.00


Skills Desired


  • Artificial Intelligence (AI)

  • Biostatistics

  • Change Management

  • Curious Mindset

  • Data Governance

  • Data Literacy

  • Data Quality

  • Data Science

  • Data Visualization

  • Deep Learning

  • Generative AI

  • Graph Algorithms

  • Learning Agility

  • Logistic Regression Models

  • Machine Learning (ML)

  • Machine Learning Algorithms

  • Neuro-Linguistic Programming (NLP)

  • Pandas Python Library

  • Python (Programming Language)

  • R Programming

  • Stakeholder Engagement

  • Statistical Analysis

  • Structured Query Language (SQL)

  • Time Series Analysis

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