Associate Principal / Principal Computational Biologist

Dewpoint Therapeutics is a clinical-stage drug discovery biotech company translating condensate biology into innovative medicines. Biomolecular condensates are reshaping our understanding of biology, and our highly collaborative team is working to turn these insights into breakthrough therapies for some of the toughest diseases. We are seeking an exceptional Associate Principal or Principal Computational Biologist / Bioinformatics Data Scientist with deep expertise in multi-omics data analysis to support our drug discovery and development programs. In this role, you will work closely with biologists and chemists to translate complex research questions into well-designed omics studies, and you will lead the design, execution, and interpretation of bioinformatics analyses that inform program decisions. Success in this role will require both deep expertise in statistical methods for 'omics data analysis, particularly of RNA-seq and proteomics data, and the ability to interpret and distill complex results into clear, impactful insights. You will be a core member of a collaborative, cross-functional Data Science and Engineering team employing diverse methods and data modalities across the R D pipeline, from imaging and chemical structure to biostatistics and AI. This is an opportunity to have significant scientific impact in a purpose-driven, supportive startup environment, with substantial ownership and room for growth. The role reports to the Head of Data Science and Technology and is based in Boston, with the potential for hybrid work. In this role, your key responsibilities will be:

• Working with bench science colleagues to translate research questions into appropriate experiments and bioinformatics analyses
• Designing and implementing new computational approaches to analyze 'omics data in ways that address novel questions arising in our discovery and development efforts
• Running and refining bioinformatics analyses and pipelines for the analysis of 'omics data, particularly RNA-seq, Proteomics, Phospho-proteomics, and WGS data
• Integrating literature and other datasets, such as pathway / network databases, to derive biological insights and get to 'so what' results
• Synthesizing and communicating results effectively to colleagues, and iteratively refining methods based on their feedback
• Owning delivery of bioinformatics workstreams end-to-end, potentially including the mentoring and coaching of junior colleagues
• Continually learning and growing as a bioinformatician, identifying emerging methods and tools to implement where appropriate
• Contributing to developing bioinformatics and data science understanding, capabilities, and standards across the organization

Qualifications:

Role Qualifications:

• A PhD in a relevant computational field such as Bioinformatics, Computational Biology, Genomics, or a related discipline
• 4+ years of industry experience (in pharma or biotech) post-PhD in computational roles, with demonstrated impact
• Proficiency in R and/or Python, with a high level of comfort in data manipulation and analysis
• Hands-on research experience with bulk transcriptomic data, ideally also with experience of single-cell, proteomic, phosphor-proteomic, and genomic data
• Expertise in statistical methods for omics data analysis, particularly for RNA-seq and proteomics datasets (e.g., differential gene, gene-set, and pathway-level analyses), including quality control methods
• Experience integrating omics data with pathway/network datasets to draw biologically meaningful insights
• Solid understanding of molecular biology principles, ideally within a research or drug discovery setting
• Outcome-driven approach with the ability to explore alternative methods pragmatically while prioritizing high-impact solutions
• Collaborative and communicative style, adept at working with colleagues across varying levels of expertise and seniority

Beneficial:

• Experience with analysis of biomarker data from ongoing clinical trials
• Experience working in drug discovery programs in oncology, neurology, and / or metabolism
• Experience working in the cloud (AWS) and with code management tools (Git) in collaborative team environments, including with containers and workflow orchestration tools such as Nextflow
• Experience working with knowledge graphs
• Experience training and working with machine learning models