Senior Expert I, Data Science

Novartis

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$126,000–$234,000 / yr
Posted
6 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $162k
This role $180k
$97k most similar roles pay here $249k

This role pays more than 65% of similar roles. Most pay $126,800–$198,000 — the shaded band above. At the midpoint, this role pays about $180k versus about $162k 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 12 open roles on FindRole.

Listed pay typically runs $194,600–$361,400 across 12 roles with salary data.

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View all roles at Novartis

At a glance

TL;DR · Senior Expert I, Data Science

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The Senior Computational Scientist role within the Oncology Data Science group at Novartis Biomedical Research in San Diego involves collaborating with interdisciplinary teams to analyze high-dimensional biological data and develop innovative analytical methods for drug discovery. Day-to-day responsibilities include designing and interpreting genomic and phenotypic screening data, integrating multi-modal datasets, and applying advanced bioinformatics and machine learning techniques to uncover actionable insights. The ideal candidate holds a PhD in Computational Biology or related fields with expertise in cancer biology, proficiency in Python or R, and experience with AI-assisted coding tools. They should be adept at working independently, managing multiple projects, and communicating complex scientific concepts effectively. This role supports cutting-edge research in induced proximity therapeutics, aiming to identify novel targets and support patient stratification strategies for groundbreaking drug development programs.

Skills

Python R Unix/Linux Version Control Reproducible Workflows AI Machine Learning Deep Learning NLP Pandas SQL Statistical Analysis Time Series Analysis Graph Algorithms Logistic Regression Model

What you'll do

  • Lead the analysis of high-throughput genomic and phenotypic screening data to inform patient stratification.
  • Design and interpret complex biological datasets to support target identification in drug discovery.
  • Develop innovative analytical methods for integrating multi-modal preclinical datasets.
  • Apply advanced bioinformatics and machine learning approaches to uncover actionable insights.
  • Communicate integrative analyses and key findings effectively to diverse scientific teams.

What we're looking for

  • PhD in Computational Biology, Systems Biology, Bioinformatics, Data/Computer Science or related field with industry experience.
  • Strong knowledge of cancer biology and multi-modal data types such as genomics, transcriptomics, proteomics, and phenotypic screening data.
  • Proficiency in Python, R, UNIX/Linux environment, version control systems, and reproducible workflows.
  • Experience leveraging AI-assisted coding tools to accelerate data analysis and model development.
  • Demonstrated ability to work independently, prioritize tasks, manage multiple projects, and communicate complex scientific concepts effectively.
  • Familiarity with preclinical biomarker discovery and validation workflows, including survival analysis.
  • Curiosity, creativity, and a solution-oriented mindset for addressing scientific problems.

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