Position Summary
ProFound Therapeutics is seeking a pioneering Senior Scientist/Principal Scientist, Biostatistics & Computational Biology to advance the ProFoundry™ Platform through rigorous statistical modeling, inference, and translational analytics. This role is ideal for a candidate with deep expertise in biostatistics, theoretical statistics, and quantitative data analysis, who is passionate about applying statistical principles to complex biological data relevant to cardiometabolic or neurodegenerative disorders to drive therapeutic discovery. The ProFoundry Atlas—a proprietary resource of genetic, transcriptomic, proteomic, and imaging data—offers a unique opportunity to uncover novel biological insights and prioritize targets for drug development. The successful candidate will play a central role in developing statistical frameworks and analytical pipelines that support preclinical research, target validation, and portfolio decision-making.
Company Summary
ProFound Therapeutics is a privately held, early-stage biotechnology company founded by Flagship Pioneering, the creators of over 75 transformative companies including Moderna Therapeutics (NASDAQ: MRNA), Seres Therapeutics (MCRB), and Indigo Agriculture. ProFound is built on a foundation of scientific innovation and entrepreneurial spirit, with a mission to redefine the boundaries of human therapeutics.
Key Responsibilities
- Design and implement statistical models for analyzing high-dimensional biological data, including genomics, transcriptomics, proteomics, and imaging relevant to cardiometabolic or neurodegenerative disorders
- Apply principles of theoretical and applied statistics to develop novel inference methods tailored to biological questions
- Lead the development of robust, reproducible pipelines for hypothesis testing, causal inference, and predictive modeling across multi-omics datasets
- Collaborate with interdisciplinary teams to translate statistical findings into biological insights and therapeutic hypotheses
- Develop simulation frameworks and statistical benchmarking tools to evaluate model performance and data quality
- Apply advanced statistical modeling to support target discovery, prioritization, and validation, integrating multi-omics and functional data
- Design and analyze preclinical experiments, including dose-response studies, biomarker discovery, and mechanistic investigations
- Use Bayesian and frequentist frameworks to quantify uncertainty and support decision-making in early-stage drug development
- Build simulation models to assess study designs, optimize resource allocation, and forecast outcomes in preclinical pipelines
- Contribute to portfolio-level analytics, helping prioritize targets based on statistical evidence, biological plausibility, and translational potential
- Support statistical planning for in vitro and in vivo studies, including power calculations, randomization schemes, and reproducibility assessments
- Develop scoring systems and prioritization frameworks for ranking therapeutic targets using multi-dimensional data inputs
- Ensure statistical rigor in the interpretation of experimental results, guiding go/no-go decisions and milestone reviews
Minimum Qualifications
- PhD in Biostatistics, Statistics, Applied Mathematics, or a related quantitative field with 3+ years of postdoctoral or industry experience; or MS with 7+ years of relevant experience
- Strong foundation in statistical theory, including probability, inference, regression, and multivariate analysis
- Experience applying statistical methods to biological or biomedical datasets, including genomics, transcriptomics, or clinical data relevant to cardiometabolic/neurodegenerative disorders
- Proficiency in statistical programming languages (e.g., R, Python) and familiarity with statistical computing environments
- Demonstrated ability to develop and validate statistical models and algorithms for complex, high-dimensional data
- Commitment to reproducible research and collaborative problem-solving
- Excellent communication skills, with the ability to explain statistical concepts to non-statistical audiences
Preferred Qualifications
- Expertise in Bayesian statistics, hierarchical modeling, and probabilistic graphical models
- Experience with longitudinal data analysis, survival analysis, and time-to-event modeling in clinical or biomedical contexts relevant to cardiometabolic/neurodegenerative disorders
- Familiarity with causal inference frameworks, such as propensity score methods, instrumental variables, or structural equation modeling
- Knowledge of experimental design, including randomized trials, adaptive designs, and observational study methodologies
- Experience with dimension reduction techniques (e.g., factor analysis, t-SNE, UMAP) and high-dimensional inference
- Exposure to functional data analysis, spatial statistics, or statistical methods for imaging data
- Familiarity with meta-analysis, statistical harmonization, and federated data analysis across cohorts
- Experience with statistical consulting or collaboration in multidisciplinary teams, especially in biomedical or pharmaceutical settings
- Knowledge of regulatory standards and statistical considerations in drug development (e.g., FDA guidelines, ICH E9/E10)
- Experience with statistical software development, package creation in R/Python, or contributions to open-source statistical tools
- Familiarity with cloud-based statistical workflows and scalable computing (e.g., parallel processing, distributed computing frameworks)
- Experience in preclinical biostatistics, including statistical design and analysis of in vitro and in vivo studies
- Familiarity with dose-response modeling, pharmacokinetic/pharmacodynamic (PK/PD) modeling, and biomarker evaluation
- Knowledge of target validation pipelines, including CRISPR screens, RNAi, and functional genomics
- Exposure to portfolio analytics and decision-support tools used in early drug discovery
- Understanding of statistical considerations in translational research, including bridging preclinical and clinical data
- Experience with model-based prioritization frameworks, such as multi-criteria decision analysis (MCDA) or machine learning-based scoring systems
- Ability to communicate statistical findings in the context of biological relevance and therapeutic strategy
ABOUT FLAGSHIP PIONEERING:
Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.
Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.
At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.
We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.
Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.
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