Job Title

Lexeo Therapeutics is a clinical-stage genetic medicine company headquartered in New York City, pioneering cardiac genetic medicine candidates to treat the root causes of inherited cardiovascular diseases. Our lead program, LX2006, targets cardiomyopathy associated with Friedreich's Ataxia and anchors a broader pipeline addressing genetically defined conditions such as hypertrophic and arrhythmogenic cardiomyopathies. Backed by a strong financial foundation, Lexeo is positioned to translate groundbreaking science into durable clinical impact. Role SummaryThis internship sits at the intersection of artificial intelligence, machine learning, and clinical drug development. You will work directly with Lexeo's clinical and scientific leadership to design and execute data-driven analyses using real clinical study data. The overarching goal is to generate novel insights that inform our understanding of:Disease burden and progression in rare cardiovascular conditionsMechanisms of action of AAV-based gene therapies in human subjectsNovel clinical endpoints and biomarkers that could strengthen future study designsThis is hands-on, hypothesis-driven R&D work. You will not be running pre-packaged reports or prompting general-purpose AI tools - you will be building and deploying analytical pipelines, training models, and contributing to scientific interpretation alongside domain experts.Primary ResponsibilitiesWrite scripts in Python, R, SQL, and/or Cypher to extract, join, and transform clinical data from internal and external sourcesBuild and work within structured databases and data lakes to organize multi-modal clinical datasetsPerform rigorous data validation, cleaning, and QC to ensure analytical readinessTrain, validate, and deploy ML models - including supervised, unsupervised, and generative AI approaches - applied to clinical and biomarker dataApply advanced statistical techniques relevant to small-n clinical datasets, including mixed-effects models, survival analysis, and dimensionality reductionEvaluate model performance, interpretability, and clinical relevance in collaboration with scientific stakeholdersUse analytical platforms such as Power BI, Excel, and Maxis to generate summaries, dashboards, and visualizations for cross-functional audiencesSynthesize findings from LEXEO's internal clinical studies alongside relevant external data sourcesParticipate in working sessions with clinical scientists, statisticians, and CMC colleagues to discuss analytical direction and resultsRequired Skills and QualificationsCurrently enrolled in a college or university (undergraduate or graduate level) in Computer Science, AI/ML, Statistics, Biostatistics, Bioinformatics, or a related quantitative field, OR enrolled in a biological or life science program with demonstrable, substantive experience in applied ML/AI through coursework, research, or prior internshipsHands-on experience building, training, or deploying machine learning or AI models in an academic project, research lab, or prior work settingProficiency in at least one of: Python, R, SQL, or Cypher for data manipulation and analysisAbility to work independently on open-ended analytical problems, make methodological decisions, and communicate trade-offs clearlyNice to have: Familiarity with clinical or biomedical data (EHRs, biomarkers, imaging, clinical trial datasets)Experience with Power BI or similar BI/visualization platformsBackground in cardiovascular biology, rare diseases, or gene therapyPrior exposure to generative AI model development or large language model fine-tuningExperience working within regulated or GxP-adjacent data environments$50 - $50 an hourWe may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.