Senior Director, AI and Data Science (Drug Discovery and R&D Enablement)

Lexeo Therapeutics, Inc.

New York (NY)

Hybride

USD 190 000 - 250 000

Plein temps

Il y a 3 jours
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Hybrid work model

Résumé du poste

Lexeo Therapeutics, Inc. is seeking a Senior Director of AI/ML to set strategy and deliver applied AI/ML solutions across discovery, development, and operations.

You will lead enterprise-scale modeling using real-world biopharma data, partnering with scientists and external vendors to raise decision confidence and accelerate outputs. This hands-on leader will build, validate, and operationalize models, drive governance for model lifecycles, and guide synthetic control and small-data approaches

Qualifications

  • PhD preferred; MS with exceptional experience considered.
  • 10+ years in applied data science/ML in life sciences/biopharma or adjacent with drug discovery translation.
  • 5+ years leading teams and influencing senior stakeholders.
  • Deep familiarity with ML methods (XGBoost, RF, SVMs).
  • Experience building predictive models from real-world data and deploying to production.
  • Strong cross-functional communication with scientists, engineers, and executives.

Responsabilités

  • Define and execute Lexeo’s AI/ML roadmap across discovery and development.
  • Deliver internal decision support and external-facing analyses (dashboards, dossiers).
  • Establish model lifecycle governance, validation, and monitoring.
  • Lead development and selection of ML approaches based on data and deployment context.
  • Build predictive analytics using real-world data with robust evaluation.
  • Guide synthetic control arms and small-data strategies with rigor.
  • Translate questions into testable hypotheses with bench scientists.
  • Bridge science and data/engineering for scalable pipelines.
  • Partner with stakeholders to implement AI-enabled workflows and platforms.

Connaissances

Advanced ML methods
Cross-functional communication
Production-model deployment

Formation

PhD in quantitative/scientific discipline
MS with exceptional experience considered

Description du poste

Role Summary

Lexeo is at an inflection point where AI and advanced analytics can materially accelerate decision-making across discovery, development, and operational execution. This Sr. Director will set direction and deliver applied AI/ML solutions across internal workflows and externally facing outputs, ranging from R&D insights to partner-ready analyses, while partnering closely with scientific teams and, when needed, external vendors/partners to solve real problems. This role is intentionally hands-on and outcome-driven: a leader who can build, validate, and operationalize models using real-world biopharma data to raise the signal-to-noise ratio in small or unstructured datasets (including synthetic control arm approaches where appropriate).

Key Responsibilities
AI/ML Strategy + Delivery
  • Define and execute Lexeo’s applied AI/ML roadmap across discovery and development, prioritizing use cases that improve speed, quality, and decision confidence.
  • Deliver solutions that are internal-only (e.g., scientific decision support, operational forecasting) and those that are generated internally but external-facing (e.g., partner-ready analyses (regulatory dossiers, briefing books, protocols etc.), validated dashboards, and decision materials).
  • Establish best practices for model lifecycle management (validation, documentation, monitoring, retraining), especially where outputs influence scientific decisions or regulated workflows.
Advanced Analytics + Predictive Modeling
  • Lead development and selection of appropriate ML approaches (e.g., XGBoost, Random Forest, SVMs, and other advanced models) based on problem framing, data constraints, interpretability needs, and deployment context.
  • Build and oversee predictive analytics using real-world data, including robust evaluation design, bias/variance trade-offs, and performance monitoring.
Small Data Excellence + Synthetic Controls
  • Apply techniques to amplify signal-to-noise in smaller datasets (e.g., regularization, Bayesian methods, hierarchical modeling, augmentation, multimodal integration, careful feature engineering, uncertainty quantification).
  • Guide strategy for synthetic control arms and comparable approaches (as appropriate), ensuring methodological rigor, transparency, and fit-for-purpose use in decision-based.
Drug Discovery / Translational Partnership
  • Translate drug discovery and translational questions into testable analytical hypotheses; partner with bench scientists to design data capture that enables strong modeling.
  • Serve as a bridge between scientific teams and data/engineering, ensuring solutions are scientifically credible and operationally adoptable.
Cross-functional Enablement + Platform Integration
  • Partner with stakeholders across R&D, CMC, Clinical, Safety, and IT/Security to implement scalable data pipelines and AI-enabled workflows.
  • Contribute leadership to current and emerging initiatives such as AI workflow automation/database buildouts and analytics agents that leverage enterprise platforms (examples already in motion include CMC AI automation, MaxisAI clinical database/AI efforts, and AI work to ingest historical data into Dataverse/Fabric for agent-based analysis; integration work such as a Benchling AI API initiative may also be in scope depending on priorities).
External Partner/Vendor Leadership
  • Liaise with external partners to evaluate tools, define statements of work, and deliver solutions—while ensuring knowledge transfer and sustainable internal ownership.
Operational Excellence
  • Improve internal processes through automation and analytics, focusing on measurable impact (cycle time, error reduction, throughput, decision latency).
  • Establish practical governance for data quality, documentation, and fit-for-use standards aligned with the realities of biopharma environments (including where regulated practices apply).
What Success Looks like (First 6-12 Months)
  • A prioritized AI/analytics roadmap tied to measurable R&D outcomes; clear ownership and delivery cadence.
  • 2-4 production-grade analytics solutions adopted by teams (internal and/or external-facing outputs as needed).
  • A repeatable approach for small datasets and high-noise signals; documented modeling standards and review practices.
  • Strong partner engagement model: vendors/partners used strategically, with internal capability building and durable outcomes.
Required Skills and Qualifications
  • Advanced degree in a quantitative or scientific discipline (PhD strongly preferred; MS with exceptional experience considered).
  • 10+ years of relevant experience across applied data science/ML in life sciences/biopharma (or adjacent domain with direct drug discovery translation), including 5+ years leading teams and influencing senior stakeholders.
  • Deep familiarity with advanced ML methods (including XGBoost, Random Forest, SVMs) and the judgment to select and justify the right tool for the job.
  • Demonstrated experience building predictive models with real-world, imperfect datasets and delivering them into production or decision workflows.
  • Proven ability to improve processes and operationalize analytics—moving beyond prototypes to adoption.
  • Strong cross-functional communication: can partner with scientists, engineers, and executives; can explain model performance and limitations clearly.
Preferred Skills and Qualifications
  • Direct experience in drug discovery, translational research, and/or R&D decision support (target ID/validation, MoA, biomarker strategy, preclinical data integration).
  • Experience with small data strategies, causality-aware thinking, and synthetic control arms or closely related methodologies.
  • Experience operating in regulated/quality-sensitive environments and building documentation practices that scale (particularly relevant where validation and traceability are required).
  • Familiarity with enterprise data platforms and modern analytics stacks (lakehouse/warehouse patterns, feature stores, MLOps, model monitoring).
About Lexeo

Lexeo Therapeutics is a New York City-based, clinical stage company dedicated to reshaping the path of genetic disease. By advancing pioneering science, Lexeo seeks to set a new standard in the treatment of cardiovascular and neurological genetic diseases, charting the path to patient outcomes once thought out of reach. The Company is advancing a portfolio of therapeutic candidates designed to address the underlying genetic causes of disease, including LX2006 for Friedreich ataxia (FA), LX2020 for plakophilin-2 (PKP2) arrhythmogenic cardiomyopathy, and others in devastating diseases with high unmet need.

Our work culture is a hybrid model with 2 days/week in the New York City office and 3 days working from home.

Lexeo Therapeutics is an EEO employer committed to an exciting, diverse, and enriching work environment.

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