Associate Director, Data Science, Computational Biology

Parabilis Medicines • Cambridge, MA

7d • $175,000 - $220,000 • Onsite

About The Position

Why Join Us? Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines that unlock high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead candidate, FOG-001, is the first direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in colorectal cancer, desmoid tumors, and a range of other Wnt/β-catenin-driven tumors. Parabilis is also advancing investigational degraders of ERG and ARON for the treatment of prostate cancer, as well as other preclinical programs. What’s the opportunity? This role is the primary computational partner for one or more pipeline programs, working across both preclinical and clinical spaces to convert complex biomarker, mechanistic, and RWD/E datasets into clear, actionable insights for target, dose, indication, and combination strategy. Reporting to the Head of Computational Biology, a successful candidate will design and implement robust analysis workflows spanning in vitro and in vivo studies, early‑phase trials, and external data sources to refine patient selection and mechanism‑of-action understanding. The ideal candidate will couple their prior experience in oncology with a deep understanding of bioinformatics methodologies, a strong computational skill set, and an ability to translate scientific challenges into technical solutions and analysis that informs team decisions. Scope of the role: Strategic thinker, planner and implementer of computational biomarker and translational analyses for early‑phase oncology studies (e.g., FOG‑001 and ERG/AR degraders), from IND‑enabling work through Phase 1/2, ensuring continuity between preclinical and clinical datasets. Design and execute analysis plans for diverse biomarker modalities across preclinical models and clinical samples, including bulk and single‑cell RNA‑seq, DNA panels/WES, ctDNA, IHC/IF, multiplex protein assays, and other exploratory readouts. Synthesize, summarize and communicate findings in a clear, decision‑oriented manner to cross‑functional teams and governance, and contribute to internal decision making, conference abstracts, and manuscripts as appropriate. Who you’ll be working with: Partner closely with discovery biology, translational scientists, clinicians, biostatistics, and RWD/E colleagues to define questions that leverage both preclinical and human data, and to design analyses that are statistically and biologically robust

Requirements

• PhD in Computational Biology, Bioinformatics, Statistics, Epidemiology, or related field, or MS with significant industry experience in translational, clinical biomarker, and/or RWD/E analysis in oncology.
• 7+ years of relevant post graduate experience (biotech/pharma or closely related), including direct work with both preclinical and clinical oncology datasets.
• Strong hands on experience analyzing biomarker data such as DNA sequencing, RNA seq (bulk and/or single cell), ctDNA, and tissue based assays (IHC/IF, multiplex platforms), with demonstrated impact on either discovery or development decisions, ideally both.
• Proficiency in Python and/or R, including data wrangling, statistical modeling, visualization, and best practices for reproducible research (version control, environments, documentation).
• Comfortable operating at the interface of discovery, translation, clinical development, and external data, with a track record of effective collaboration with non-computational colleagues.
• Excellent communication skills, with the ability to translate complex analyses into concise, decision ready narratives for diverse audiences.
• Demonstrated use of AI tools in your current role and responsibilities is required.
• Able to work on-site and attend in-person meetings for the majority of time.

Nice To Haves

• Advanced or innovative use of AI is a strong plus.

Responsibilities

• Analyze preclinical in vitro and in vivo data (e.g., Helicon screens, xenograft/PDX models, pharmacology and PD studies) to characterize target engagement, pathway modulation, and resistance mechanisms, and translate these findings into clinical hypotheses.
• Analyze pre and on treatment patient biopsies and blood samples to quantify pathway modulation, signaling changes, and emergent resistance or sensitivity signatures, integrating with preclinical findings where possible.
• Develop, validate, and operationalize predictive and pharmacodynamic biomarker signatures for use in preclinical strategy, trial design, and RWD/E anchored analyses, including patient stratification and indication/expansion cohort selection
• Uses leading-edge knowledge of principles, concepts and practices and/or techniques to lead complex projects involving related departments
• May have supervisory responsibilities

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Ph.D. or professional degree