Pioneering Medicines: Principal Scientist Bioinformatics

Flagship Pioneering•Cambridge, MA

58d•$148,000 - $203,500

About The Position

Pioneering Medicines, a division of Flagship Pioneering, is building a world-class biopharmaceutical R&D capability focused on conceiving and developing life-changing treatments for patients by harnessing the power of Flagship's scientific platforms and applying those innovative approaches to serious diseases with unmet medical need. Unique to Pioneering Medicines’ approach is the opportunity to combine platforms to create truly novel and potentially transformative treatments. About Flagship Pioneering: Flagship Pioneering conceives, creates, resources, and develops first-in-category life science platform companies to transform human health and sustainability. Since its founding in 2000, the firm has originated and fostered the development of more than 100 scientific ventures, resulting in over $34 billion in aggregate value, 500+ issued patents, and more than 50 clinical trials for novel therapeutic agents. Position Summary: We are seeking a highly capable bioinformatics expert at the Principal Scientist level, with experience in applying computational methods to biological data, to join our Translational Sciences team. The successful candidate will step into active therapeutic programs and operate with a high degree of independence, helping drive bioinformatics strategy from early discovery through translational development. This role is well-suited for individuals who combine scientific depth with strong computational acumen and thrive in dynamic, cross-functional environments. The position offers room for growth, with flexibility to consider more senior candidates who demonstrate the ability to lead program-level bioinformatics strategy and cross-functional integration.

Requirements

Ph.D. in Bioinformatics, Computational Biology, Biological Sciences, Computer Science, or related field.
8+ years of relevant industry experience, ideally with direct exposure to therapeutic discovery programs.
Understanding of biology and/or translational research and ability to address biological questions using computational approaches.
Strong experience analyzing next-generation sequencing data (e.g., bulk/single-cell RNA-seq, WGS/WES, ATAC-seq).
Proficiency in Python and/or R, and experience with cloud-based computing (AWS, Terra, Code Ocean).
Demonstrated application of AI/ML to biological datasets, including algorithm development or use of libraries like scikit-learn, XGBoost, Pinnacle.
Familiarity with biological interpretation of omics data, pathway analysis, and network inference.
Ability to work independently, manage priorities across programs, and influence program strategy.
Excellent communication and collaboration skills; experience working in matrixed teams.

Nice To Haves

Exposure to translational science, patient stratification, or biomarker discovery in preclinical or clinical contexts.
Experience integrating heterogeneous omics data.
Knowledge of experimental design and data QC best practices.
Prior experience in biotech or pharma.

Responsibilities

Lead computational biology efforts within active therapeutic programs, working across disease areas such as oncology, immunology, metabolic, or rare diseases.
Analyze and integrate omics data types (e.g., bulk/single-cell RNA-seq, proteomics, spatial transcriptomics, genomic variation) to inform target discovery, biomarker development, and patient segmentation.
Translate biological questions into analytical strategies, influence experimental design, and generate actionable insights for interdisciplinary teams.
Coach other team members on strategic thinking and next level synthesis and communication skills.
Apply machine learning and AI approaches to uncover novel insights, including dimensionality reduction, clustering, classification, predictive modeling, and network-based inference.
Stay current with relevant computational trends (e.g., multi-modal learning, foundation models, causal inference) and propose their application to Pioneering Medicines programs.
Communicate findings effectively to both technical and non-technical stakeholders, contributing to program direction and decision-making.
Serve as a computational thought partner to scientific leadership across programs.