Salesforce Developer

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

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

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.

Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture