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# Salesforce Developer

- **Company:** CareerCircle
- **Location:** San Diego, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $234,000.0
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Data Analysis, Systems Engineering, ArcGIS (Software), Automation of Tests, Bioinformatics, C++ (Programming Language), Computational Biology, Information Engineering, Data Mining, Embedded Software, R (Programming Language), Python (Programming Language), Machine Learning, Modular Design, Cyber-physical Systems, Signal Processing, Software Engineering, Spatial Data Infrastructures, Systems Modeling Language, Web Applications, Data Processing, Large Language Models, Deep Learning, Information Technology, Restful APIs, Software Version Control, Databricks, Programming Languages
- **Published:** August 19, 2026
- **Apply:** https://www.careercircle.com/jobs/all/all/usa/all/all/e0d9b41d-adbc-4459-88bf-1922cfc35ce8

## About the Role

Linux
Biology
Oncology
Genomics
Innovation
Creativity
Biomarkers
Proteomics
Data Types
Data Mining
Data Science
Pharmacology
Communication
Data Analysis
Cancer Biology
Drug Discovery
Bioinformatics
Self-Motivation
Version Control
Systems Biology
English Language
Computer Science
Drug Development
Machine Learning
Data Engineering
Medical Research
Clinical Research
Survival Analysis
Solution-Oriented
Analytical Method
Advanced Analytics
Workflow Management
Programming Languages, * PhD in Computational Biology, System Biology, Bioinformatics, Data/Computer Science, or related field with relevant industry experience.

 * Strong knowledge of cancer biology and multi-modal data types such as genomics, transcriptomics, proteomics and phenotypic screening data.
Proficiency in one or more programming languages for bioinformatics applications (e.g., Python, R) with experience in UNIX/Linux environment, version control, and reproducible workflows.
Demonstrated statistical rigor and analytic depth in the analysis of high-dimensional omics datasets (e.g., bulk and single-cell transcriptomics, genomics).

 * Demonstrated experience leveraging AI-assisted coding tools (e.g., copilots, code generators, and LLM-based workflows) to accelerate data analysis, model development, and reproducible scientific pipelines.
 * Familiarity with data workflows, including preclinical biomarker discovery and validation; survival analysis is a plus.
 * Proven ability to work independently, prioritize tasks effectively, define next steps and manage multiple projects and stakeholders in a fast-paced environment.
 * Excellent communication skills, with the ability to deliver complex scientific concepts to diverse audiences.
Curiosity, creativity and a solution-oriented mindset when addressing scientific problems.
Fluency in English (written and verbal)., Tooling
Biology, Physics
Planning
Oncology
Research
Medicare
Medicaid
AI Agents
Innovation
Immunology
Statistics
Caregiving
Proteomics
Testability
Probability
Data Science
Communication
Data Analysis
Data Modeling
Deep Learning
Prioritization
Drug Discovery
Modular Design
Histopathology
Medical Records
Version Control
Test Automation
Trustworthiness
Real World Data
Data Processing
German Language
Computer Science
Drug Development
Causal Inference
Machine Learning
Data Engineering
Thought Leadership
Workflow Management
Infectious Diseases
Functional Genomics
Time Off Management
Software Engineering
Statistical Modeling
Technical Leadership
Collective Bargaining
Postdoctoral Research
Computational Biology
Artificial Intelligence
R (Programming Language)
Authorization (Computing)
Verbal Communication Skills
Python (Programming Language)
Medical History Documentation

## Description

Position Location: onsite, San Diego, CA #LI-hybrid *This role is based in San Diego, CA. Please only apply if this location is accessible for you. The Oncology Data Science group within Biomedical Research supports the Oncology Disease Area with computational biology, Artificial Intelligence / Machine Learning (AI/ML), and data engineering for novel therapeutics across multiple drug modalities. As integrated scientists and engineers, we apply advanced analytics to pre-clinical and clinical projects, enabling progress in target discovery, drug development, and translational and clinical science. Help us bring innovative drugs to the clinic by analyzing and interpreting multi-dimensional molecular data ('omics) into target identification, drug development, and patient biomarker discovery. The Low Molecular Weight (LMW) team at Novartis Biomedical Research Oncology Data Science is seeking a highly motivated Senior Computational Scientist to join our team. With a focus on induced proximity
therapeutics, you will collaborate with cross-functional teams in Biomedical Research and Oncology stakeholders to advance efforts in target identification and drug development to support our ground-breaking drug discovery programs.

About the Role

Major accountabilities:

 * Collaborate closely with interdisciplinary wet-lab and computational scientists to design, analyze, and interpret high-dimensional biological data (e.g., bulk RNA-seq, DNA-seq, CRISPR, drug screening) to inform critical project decision.
 * Lead profiling strategies and analysis of high-throughput genomic and phenotypic screening data to inform patient stratification and mechanism of resistance, in support of drug discovery and development.
 * Integrate multi-modal internal and external preclinical datasets (e.g., genomics, transcriptomics, pharmacology, and functional screens) to produce translationally relevant insights.
Apply advanced bioinformatics and machine learning approaches across multi-modal datasets to uncover novel, actionable biological insights and therapeutic hypotheses.

 * Develop and implement innovative analytical methods to support emerging technologies and to effectively integrate, interrogate, and visualize multi-dimensional datasets.
 * Drive oncology research by leveraging data mining and genomic profiling to identify novel targets for induced proximity modality, elucidate mechanism of action and support patient stratification strategies.
 * Communicate integrative analyses and key findings clearly and effectively to diverse audiences, including cross-functional scientific teams and stakeholders., Dashboard
Pipelines
Operations
Automation
Databricks
Scalability
RESTful API
Data Science
Geoprocessing
Web Applications
Spatial Analysis
Advanced Analytics
Business Valuation
Technical Standard
Workflow Management
ArcGIS (GIS Software)
Full Stack Development
Artificial Intelligence
Business Transformation
Business Continuity Planning
Spatial Data Infrastructures
Python (Programming Language)
Application Programming Interface (API)
+0
Model Based Systems Engineer
Actalent

Woburn, MA*Remote

Radar
Planning
Research
Visionary
Innovation
Testability
Simulations
Communication
Collaboration
Detail Oriented
Agile Methodology
Embedded Software
Signal Processing
Electronic Warfare
Systems Engineering
Resource Management
Software Development
Aerospace Engineering
Requirements Analysis
Cyber-Physical Systems
Artificial Intelligence
Technical Documentation
C (Programming Language)
Systems Modeling Language
Digital Signal Processing
Quality Management Systems
Engineering Design Process
Agile Software Development
C++ (Programming Language)
Python (Programming Language)
Unmanned Aerial Systems (UAS)
Model Based Systems Engineering
+0


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