About HAYA Therapeutics
At HAYA Therapeutics, we are revolutionizing RNA-guided genome-targeting therapies to treat fibrosis, heart failure, and other serious chronic diseases associated with aging. Our innovative platform leverages long non-coding RNAs (lncRNAs) - key regulators within the “dark matter” of the genome - to develop first-in-class, highly specific therapies that reprogram disease-driving cell states into a healthy and resilient state, tackling disease at its roots.
Following the successful close of our Series A financing, HAYA is well-positioned to advance our pipeline and execute on key scientific and operational milestones, including the advancement of HAYA’s lead program, HTX-001, toward the clinic for the treatment of non-obstructive hypertrophic cardiomyopathy (nHCM).
In recognition of our scientific innovation and potential global impact, we have been named one of the 100 early-stage companies selected for the World Economic Forum’s 2025 Technology Pioneers.
As a fast-growing biotech, we offer an entrepreneurial, science-driven environment where you’ll have a direct impact on shaping our programs and advancing the future of RNA medicine.
Position Summary
HAYA Therapeutics is seeking a highly experienced, senior-level data science leader to take a prominent and highly visible role within the Data Science team. This position exists to ensure that complex preclinical and translational datasets are transformed into high-quality, decision-ready scientific outputs that support program advancement, platform positioning, and external engagement.
In this strategic role, you will act as a scientific gatekeeper for data and materials generated in the cardiac and cardiorenal space, ensuring rigor, consistency, and scientific credibility across multiple therapeutic programs.
You will serve as a senior scientific authority at the interface of computational biology and cardiac disease biology. Acting as a bridge between data science and biology, you will apply deep domain knowledge and multi-omics expertise to interpret complex datasets, guide analytical strategy, and ensure biological accuracy and translational relevance.
This role requires strong judgment, autonomy, and the ability to set analytical standards, particularly for cardiac-focused preclinical and translational research, while partnering closely with biology, translational, and clinical stakeholders.
A core component of this role is creating and owning high-impact scientific content and narratives for board-level discussions, alliance management, and business development. You will take complex, multi-layered scientific analyses and translate them into clear, compelling stories that explain the “why,” “so what,” and strategic implications behind the data.
This role requires the ability to frame scientific results within a broader platform and program context, connecting individual analyses into coherent narratives that articulate the value, differentiation, and trajectory of HAYA’s science. You will ensure that all scientific storytelling is accurate, rigorous, and aligned with the company’s strategic objectives.
You will play a highly visible role in representing HAYA’s scientific capabilities to internal leadership and external partners, tailoring scientific stories for senior technical and non-technical audiences while maintaining the highest standards of scientific integrity.
What’s in it for me?
This role offers a rare opportunity to operate at the intersection of science and business, serving as a bridge between complex biological data and strategic decision-making. You will not only analyze and interpret science, but also shape how HAYA’s platform, programs, and data are translated into clear narratives that inform leadership, partners, and investors.
Your work will directly influence program direction, business development opportunities, and how the company’s scientific value is communicated externally. This is a highly visible role with meaningful exposure across the organization and to external stakeholders, set within a collaborative and innovative culture that values scientific curiosity, sound judgment, and ownership, and supports your continued growth as a senior scientific leader.
Key Responsibilities
Scientific Leadership & Platform Showcasing
- Stakeholder Engagement: Act as a lead scientific communicator, showcasing HAYA’s data science platform and analytical capabilities to external partners, investors, and at scientific conferences.
- Strategic Material Generation: Drive the creation of high-quality, high-impact data packages and visualizations from analyses across multiple programs to support decision-making and external business development.
- Gatekeeper Function: Serve as the quality control gatekeeper for all outgoing material in the cardio-renal-metabolic context; review and validate computational outputs to ensure biological accuracy and rigorous standards before dissemination.
- Translational Biomarker Strategy
- Biomarker Identification: Lead the computational strategy for prioritizing pharmacodynamic (PD), predictive, and prognostic biomarkers from multi-omics datasets to support clinical development in the Cardio-Renal-Metabolic space.
- Translational Bridge: Define and execute the data strategy to translate preclinical findings (in vitro/in vivo) into clinically relevant hypotheses, ensuring alignment with industrial drug development standards.
- Patient Stratification: Apply advanced statistical and machine learning approaches to stratify patient populations and define responder signatures for HAYA’s therapeutics in heart failure and related metabolic conditions.
Computational Biology
- CRM-Focused Analysis: Perform and oversee end-to-end analysis of bulk, single-cell, and single-nuclei transcriptomics and epigenomics data, acting as a subject matter expert specifically within cardiac, renal, and metabolic areas.
- Multi-omics Integration: Integrate multi-omics data from in-house and public sources to uncover novel biology, disease-specific cell states, and perturbation signatures relevant to cardiac diseases (e.g., HCM, HF).
- Methodological Standards: Establish analysis strategies to handle translational datasets, setting the standard for the entire team.
Cross-Functional Collaboration
- Narrative Construction: Synthesize data from multiple independent datasets to construct clear, biologically meaningful narratives for technical and non-technical audiences.
- High Autonomy & Ownership: Be able to drive high-quality material generation autonomously, taking over major responsibilities from other team members.
Education & Experience
- Education:
- PhD in computational sciences (e.g., bioinformatics, computer science) or life sciences with a strong computational focus.
- Experience Level:
- Senior Scientist II: 6+ years of relevant industry post-doctoral experience.
- Technical Expertise:
- Expertise with the biological interpretation of multi-omics transcriptomic data (single-cell/nuclei RNA-Seq and bulk RNA-Seq in particular).
- Proficiency in R or Python and data science frameworks: HPC/cloud-based environments, Jupyter notebooks, Ai-augmented data science (e.g., Cursor, Windsurf).
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- Biomarker Workflows: Demonstrated industrial experience in computational biomarker discovery pipelines, including feature selection, validation, and clinical utility assessment.
- Experience with epigenomic data (e.g., ATAC-Seq, CUT&RUN) is highly desirable.
- Experience with ASO / siRNA-related data interpretation is highly desirable.
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- Industrial CRM Expertise: Comprehensive experience with translational and industrial/biotech settings in the Cardio-Renal-Metabolic therapeutic area.
- Translational Insight: Proven ability to bridge the gap between early discovery and clinical translation, utilizing computational biology to support target and biomarker validation and translation.
- Communication:
- Exceptional ability to present complex data to diverse audiences (business, clinical, scientific) and experience acting as a reviewer/approver for scientific content.
- Exceptional ability to generate high-quality data packages and results for internal and external audiences in an autonomous way.
