Principal Scientist, Translational Data Science

Principal Scientist, Translational Data Science Cambridge Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines for patients with serious diseases by unlocking biologically important targets long considered undruggable. The company has pioneered a new class of alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that have historically been beyond the reach of conventional medicines. The company's lead investigational medicine, zolucatetide, is the first and only direct inhibitor of the β-catenin:TCF interaction, a central node in the Wnt/β-catenin pathway that has eluded drug developers for decades. Zolucatetide is being evaluated in the clinic across multiple Wnt/β-catenin-driven diseases, including desmoid tumors, familial adenomatous polyposis (FAP) and a range of other solid tumor indications. Beyond zolucatetide, Parabilis is advancing additional Helicon-based programs focused on other challenging targets where we believe our medicines could have life-altering impact. This role is a senior scientific leader within Translational Medicine responsible for applying computational biology and human disease data to identify, credential, and advance new therapeutic opportunities. You will serve as the lead Translational Data Scientist for preclinical Projects, from target identification and credentialing through lead optimization. You will define the computational strategy, identify the critical questions and analyses needed to drive Project decisions, and integrate internal and external data to establish target rationale, disease context, mechanism of action, and biomarker and indication hypotheses. As Projects transition into development Programs, you will partner with the Program Lead Data Scientist, who leads computational strategy through IND-enabling activities and Phase 1/2 development. You will support Program analyses and ensure continuity of biological hypotheses, biomarkers, data, and insights from discovery into development. The ideal candidate combines deep computational expertise and oncology biology with strong scientific judgment and the ability to translate complex data into clear, actionable recommendations. Scope of the role: Lead Translational Data Science for preclinical Projects from target identification and credentialing through lead optimization. Define computational strategies that address critical Project decisions around target rationale, disease context, mechanism, biomarkers, indications, combinations, and resistance. Integrate human genetics, tumor genomics, functional genomics, molecular profiling, preclinical studies, and other internal and external data to build a coherent body of evidence supporting Project decisions. Partner with experimental scientists to translate computational findings into testable hypotheses and prioritize experiments and analyses that address critical Project questions. Establish translational and biomarker hypotheses that can follow an asset from discovery into clinical development. Lead the computational transition from Project to Program, transferring scientific rationale, data, analytical frameworks, biomarkers, and outstanding questions to the Program Lead Data Scientist. Support Programs under the direction of the Program Lead Data Scientist, contributing computational and biological expertise to IND-enabling and Phase 1/2 activities. Communicate integrated findings and recommendations to Project teams, Program teams, senior leadership, and governance. Who you'll be working with: For Projects, you will be the lead Translational Data Scientist, partnering with Project leadership and colleagues across discovery biology, pharmacology, translational medicine, pathology, chemistry, protein sciences, and other disciplines. You will work closely with experimental scientists to create an iterative cycle in which computational analyses guide experiments and experimental results refine biological hypotheses. As a Project transitions to a Program, you will partner closely with the Program Lead Data Scientist to ensure continuity of scientific rationale, biomarkers, data, and unresolved questions. For Programs, you will work in support of the Program Lead Data Scientist, collaborating with translational scientists, clinicians, biostatisticians, biomarker scientists, pathology, RWD/E colleagues, and other functions to connect emerging development and clinical observations with the underlying biology and preclinical evidence. Main tasks & duties for the position: Lead computational analyses supporting target identification and credentialing using tumor genomics, transcriptomics, functional genomics, human genetics, single-cell/spatial data, and relevant clinical and epidemiological datasets. Analyze internal in vitro and in vivo studies to characterize target engagement, mechanism of action, response determinants, and resistance mechanisms. Integrate preclinical findings with human disease data to refine indication, patient-selection, biomarker, and combination hypotheses. Develop predictive and pharmacodynamic biomarker hypotheses that can be translated from Projects into Programs. Design statistically rigorous, reproducible analyses across multimodal oncology datasets, including DNA sequencing, bulk and single-cell RNA-seq, functional genomic screens, imaging, and other emerging data types. Distinguish exploratory findings from evidence sufficient to drive decisions and identify additional analyses or experiments needed to resolve key uncertainties. Present concise, decision-oriented recommendations to scientific teams, leadership, and governance. Advance computational approaches and best practices across Translational Data Science and provide scientific and technical mentorship to colleagues. What you'll need to be successful: PhD in Computational Biology, Bioinformatics, Systems Biology, Genomics, Statistics, or a related quantitative field, with significant 10+ years of relevant industry experience. Deep expertise in cancer biology and applying computational approaches to oncology drug discovery and translational research. Demonstrated impact on target identification/credentialing, mechanism-of-action, biomarker, or drug-development decisions. Strong experience integrating multimodal biological data, such as tumor genomics, bulk and single-cell transcriptomics, functional genomics, human genetics, proteomics, imaging, and preclinical pharmacology. Strong proficiency in Python and/or R and reproducible computational research practices. Ability to identify and prioritize analyses that address critical scientific and Project decisions. Demonstrated ability to lead complex multidisciplinary scientific work through influence and collaboration. Strong partnership with experimental scientists and ability to translate computational findings into testable biological hypotheses. Excellent communication skills and ability to synthesize complex evidence into concise, decision-ready recommendations. Demonstrated use of AI tools in current scientific responsibilities; advanced or innovative applications of AI to computational biology and drug discovery are a plus. Able to work on-site and attend in-person meetings for the majority of time. Core Values Parabilis Medicines is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit. Growth-Minded . We're inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable. In(ter)dependent. We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options. Patient-focused. We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact. All-In. We're All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history. The base salary range for this position is $215,000-$245,000, depending on experience, qualifications, and internal practices. Parabilis's total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees' overall well-being. As an equal opportunity employer, Parabilis Medicines values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law. Parabilis Medicines