Careers

Primary Responsibilities

Author statistical analysis plans in conjunction with the clinical team
Responsible for biostatistical activities for a complex portfolio of clinical studies for gene therapy programs.
Where applicable, oversees and directs statistical analysis, document review and data inclusion for NDA submissions of assigned studies by collaborating with own team, other Biostatistics team members, CROs, and cross-functional partners. Ensures appropriate statistical consultation on trial design and study endpoints and timely and well-executed authoring of statistical analysis plans.
Align the requirements for data reporting, tables, listings, and figures required for interim and final reports, including topline reports and final clinical study reports.
Where applicable, oversees, and contributes to completion of all technical and operational statistical activities for a portfolio of clinical trials. Directs internal and external teams in the definition, execution and completion of statistical activities for disease or therapeutic area products of considerable complexity.
Contribute to clinical study designs and clinical development planning for the portfolio.
Where applicable, advises or otherwise ensures timely and appropriate advice to internal and external partners on statistical analysis strategies, reliability of measurements and identifiability of models, and interpretation and presentation of statistical results.
Ensures timely and appropriate gathering, organization, and analysis of different data sources to enable delivery of the statistical analysis plan and clinical study endpoints for clinical studies.
Reviews and approves biostatistical input into clinical development documentation, scientific publications and presentations and regulatory documentation.
Typically takes a lead in special projects that can benefit multiple biostatistics team members, such as new methodologies, processes, technology and other tools, and may also lead the development and / or implementation of SOPs and related documentation.
Provide statistical leadership in clinical study team setting.
May independently present at department, project team, or Sr. Management meetings.
Adheres to regulatory requirements of study conduct, statistical analysis principles, industry standards, and LEXEO’s SOPs. 

Required Skills and Qualifications

• PhD in biostatistics or related discipline with 8+ years (10+ years with MS) relevant experience in statistical analysis of biomedical data using SAS or equivalent software in the biopharma industry or a related environment 
• Extensive biomedical statistical analysis experience and experience working with relevant software.
• Experience developing software and other tools to support statistical analysis of biomedical or related data. Strong proficiencies in software and other tools used typically used by Biostatistics.
• Demonstrated excellence in complex project management and effectively managing multiple projects and priorities.
• Experience working with CROs for data and programming deliverables.
• Experience leveraging AI and machine learning to enhance clinical trial design, analyses and decision-making is preferred.
• Expert-level of knowledge of biostatistics, as evidenced by independence in assuming responsibilities for complex Phase 1-3 gene therapy projects.
• Extensive knowledge of statistical designs, applicable to clinical trials in rare disease which allow for robust study results in smaller datasets.
• Demonstrates strategic thinking in advising others on statistical requirements and opportunities to improve study or other project outcomes.
• In-depth understanding of the cross-functional roles and responsibilities involved in drug development.
• Knowledge of FDA and EMA regulations, ICH guidelines, GCP and familiarity with standard clinical procedures.
• Strong communication and organizational skills.
• Demonstrable abilities to effectively communicate project direction and status to varying organizational levels, including leadership teams, executives, and steering committees.
• Ability to handle multiple development programs simultaneously.
• Excellent teamwork, organizational, interpersonal, conflict resolution and problem-solving skills.
• Excellent written and verbal communication skills demonstrated by ability to present clear instruction/direction.
• Analytical and problem-solving capabilities.
• Collaborative and collegial work style.
• Attention to detail and follow-up.

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-making. 

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).

Primary Responsibilities

Assist in managing day‑to‑day lab operations, including inventory management, consumables ordering, managing a stock room, and equipment maintenance
Maintain digital inventory of supplies, reagents, and equipment. Place orders and track deliveries
Oversee equipment maintenance, calibration, and service records to ensure operational readiness
Support onboarding and continuous training of laboratory staff on lab procedures and safety protocols
Monitor the environmental elements of the laboratory with safety regulations, institutional policies, and quality standards
Help develop and update standard operating procedures (SOPs) and documentation
Coordinate shipping samples, supplies, and reagents to/from a biorepository, CDMOs, and the Lexeo lab
Coordinate waste disposal, chemical storage, and safety inspections
Serve as a point of contact for vendors, facilities, and service technicians
Actively collaborate and communicate cross-functionally within Lexeo. 
The successful candidate will embrace this challenging role with enthusiasm, demonstrate the ability to work within a team, and maintain professionalism while getting things done quickly and efficiently. Attention to detail is expected. The ability to juggle many task at the same time meticulous and detail-oriented approach is crucial for maintaining accuracy.

Required Skills and Qualifications

Bachelor’s or Master's degree in a scientific discipline (e.g Biology, Chemistry,  Biotechnology)
5 years of relevant experience in lab operations (in industry or in combination with academia) with a deep understanding of lab safety
Hands-on experience in a pharmaceutical/biotech environment; knowledge of gene therapy basis a plus
Strong organizational skills with attention to detail and accuracy
Ability to manage multiple priorities and meet deadlines in a fast-paced environment
Excellent communication and coordination skills
Familiarity with Benchling or Quartzy is beneficial
Ability to regularly work onsite 5 days per week

Primary Responsibilities

Manage the day‑to‑day relationship and performance of the MSP to ensure delivery of high‑quality, cost‑effective IT services
Coordinate IT equipment provisioning and maintenance for employees and contractors, including laptops, printers, and communication tools
Ensure effective IT service desk operations, user lifecycle workflows, and asset and license management
Provide direct technical support as needed to employees and consultants across the organization
Deliver IT and cybersecurity training and communicate updates, best practices, and process improvements
Perform regular account and access audits and ensure enforcement of least‑privilege principles
Manage monitoring, maintenance, and support of security tools, systems, and service provider relationships
Support development and continuous improvement of documentation, procedures, and the information security program
Partner with cross‑functional teams to identify opportunities for automation, optimization, and efficiency
Stay current on emerging technologies, cybersecurity risks, and industry best practices to make informed recommendations 

Required Skills & Qualifications

At least 6 years of experience in IT operations, including hands‑on leadership in a growing organization
Minimum of 3 years of experience in the biotechnology or pharmaceutical industry
Strong expertise in Microsoft technologies, M365, and PC environments
Solid understanding of cybersecurity principles, data privacy standards, and compliance frameworks
Experience managing IT projects and implementing infrastructure across diverse technologies
Proficiency in systems administration, networking, security tools, databases, storage systems, and communication technologies
Demonstrated ability to optimize support systems and workflows including use of responsible AI capabilities
Strong critical thinking, decision‑making, and prioritization skills
Service‑oriented mindset with excellent interpersonal, verbal, and written communication abilities