(Senior/Principal) Scientist, Neuroscience, Immunology, and CV (NIC) Translational Informatics and Predictive Sciences

Working with Us
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Job Description

We seek a creative and passionate computational biologist with a strong background in clinical data analysis to join the Neuroscience, Immunology, and Cardiovascular (NIC) Translational Informatics team within Informatics and Predictive Sciences (IPS). In this role, you will use machine learning and advanced statistical approaches to analyze high-dimensional data from late-stage clinical trials and longitudinal patient cohort profiling.

In support of late-stage portfolios in cardiovascular, immunology, and neuroscience, your responsibilities will include biomarker discovery for treatment response and resistance, patient stratification, and mechanistic analyses to advance Life Cycle Management (LCM) and indication expansion. You will also play a key role in reverse translation, leveraging clinical insights to inform early research and drive bedside-to-bench innovation beyond the current portfolio. Your work will directly contribute to the development of novel therapies for patients with cardiovascular conditions (e.g., Heart Failure with Preserved Ejection Fraction), pulmonary diseases, and neurological disorders.

Note: The final title for this position may range from Scientist to Senior Principal Scientist, depending on the candidate’s qualifications and years of relevant experience.

Key Responsibilities

• Analyze high-dimensional datasets from late-stage clinical trials and multi-modal real-world datasets from commercial partners, pre-competitive consortiums, and public resources.
• Work with diverse data modalities, including clinical data (ADaM/SDTM), high throughput proteomics (e.g., Olink, SomaScan), Whole Genome Sequencing, genotyping array, RNA-Seq and multiplex flow cytometry.
• Perform deep and innovative analyses of these data to build comprehensive understanding of disease mechanisms and patient heterogeneity, identify non-responders to standards of care with unmet medical needs, generate testable hypotheses for drug differentiation, combination strategies, and novel indication opportunities.
• Optimize reverse translation through application of late-stage clinical data sets to inform early-stage clinical trials and the discovery pipeline, in close collaboration with teams across Research and Development, including bioinformaticians, statisticians, biologists, biomarker leads, and clinicians.
• Communicate findings and recommend follow-up actions in multiple settings (including 1:1, seminars, and team meetings). Participate in authorship of scientific reports and present methods and conclusions to publishable standards.

Basic Qualifications

• Bachelor’s degree with 6+ years of academic/industry experience, or
• Master’s degree with 4+ years of experience, or
• PhD with 2+ years of experience in computational biology or a related field

Preferred Qualifications

• PhD from a recognized institution in a quantitative field such as computational biology or related
• Experience analyzing clinical data from interventional clinical trials, including integration of structured clinical endpoints (e.g., ADaM/SDTM), biomarker data (e.g., lab measures), and longitudinal assessments to support pharmacodynamic analyses, as well as the identification of predictive, prognostic, or surrogate endpoint biomarkers.
• Experience analyzing and integrating high-dimensional molecular datasets such as multi-omics (e.g., RNA-seq), single cell (scRNA-seq), genome-wide genotyping array, or spatial transcriptomics datasets