Data Science, Cheminformatics & AI, Lab-in-the-Loop Hit Finding

Novartis

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$138,600–$257,400 / 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 $172k
This role $198k
$111k most similar roles pay here $273k

This role pays more than 57% of similar roles. Most pay $126,800–$216,312 — the shaded band above. At the midpoint, this role pays about $198k versus about $172k 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 $160,300–$297,700 across 17 roles with salary data.

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View all roles at Novartis

At a glance

TL;DR · Data Science, Cheminformatics & AI, Lab-in-the-Loop Hit Finding

Role Posting Log in to save

Join Novartis’s Data Science team in Discovery Sciences as a Senior Expert II to drive the convergence of wet and dry lab practices through advanced cheminformatics, AI, and data science. You will lead the development and execution of LitL workflows, integrating model monitoring and prediction telemetry with enterprise initiatives to accelerate hit finding in early drug discovery projects. Your responsibilities include designing scalable data pipelines for high-throughput assay data, applying cutting-edge in silico methods like agentic workflows and drug-target interaction modeling, and collaborating closely with experimental and computational teams. Essential skills include a PhD or equivalent experience in cheminformatics or related fields, proficiency in Python’s scientific ecosystem, and strong Linux-based HPC and cloud computing expertise. Ideal candidates will also have experience with Make-on-Demand chemistry and virtual chemical spaces like Enamine REAL, as well as a track record of impactful publications.

Skills

Python Linux SQL Docker Kubernetes Terraform CI/CD Prometheus Grafana AWS Azure GoogleCloud PostgreSQL MongoDB Redis Git Jenkins Ansible Pandas R Scikit-learn TensorFlow PyTorch DeepLearning MachineLearning AI DataVisualization Cheminformatics AgenticWorkflows

What you'll do

  • Lead and execute data science strategy for Lab-in-the-Loop workflows to accelerate drug discovery.
  • Develop in silico hit finding strategies using internal and external compound databases.
  • Apply cutting-edge in silico methods with multi-modal data to drive early hit finding projects.
  • Design scalable data pipelines for high-throughput assay data to enable automated hit-finding workflows.
  • Champion best practices for model development, deployment, and monitoring within Lab-in-the-Loop initiatives.

What we're looking for

  • PhD in cheminformatics or chemistry with 4+ years of post-graduate experience.
  • Expertise in applying cheminformatics and machine learning to hit finding.
  • Experience with high-throughput screening technologies and advanced phenotypic screening.
  • Strong proficiency in Python scientific ecosystem, including agent-based coding.
  • Demonstrated ability to work effectively in interdisciplinary drug discovery teams.
  • Experience implementing AI in Lab-in-the-Loop workflows for early drug discovery.

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