{"id":786232,"url":"https://alion.io/job/lexeotx-senior-director-ai-and-data-science-drug-discovery-and-rd-enablement","title":"Senior Director, AI and Data Science (Drug Discovery and R&D Enablement)","company":{"id":679873,"name":"Lexeo Therapeutics","domain":"lexeotx.com","url":"https://alion.io/company/lexeotx","size_band":"201-500","is_staffing_agency":false,"is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":229500,"max":332000,"currency":"USD","period":"year","gross":null,"usd_annual":332000},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Interpretability","optional":false},{"name":"Multimodal AI","optional":false},{"name":"XGBoost","optional":false},{"name":"Feature Store","optional":true}],"status":"live","first_seen_at":"2026-03-19T23:04:22Z","employer_posted_date":"2026-03-19","last_verified_at":"2026-09-24T14:23:09Z","board_verified":true,"closed_at":null,"days_open":188,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":188},"description":"Role Summary\nLexeo 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).\nKey Responsibilities\nAI/ML Strategy + Delivery\nDefine and execute Lexeo’s applied AI/ML roadmap across discovery and development, prioritizing use cases that improve speed, quality, and decision confidence. \nDeliver 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).\nEstablish best practices for model lifecycle management (validation, documentation, monitoring, retraining), especially where outputs influence scientific decisions or regulated workflows.\nAdvanced Analytics + Predictive Modeling\nLead 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.\nBuild and oversee predictive analytics using real-world data, including robust evaluation design, bias/variance trade-offs, and performance monitoring.\nSmall Data Excellence + Synthetic Controls\nApply techniques to amplify signal-to-noise in smaller datasets (e.g., regularization, Bayesian methods, hierarchical modeling, augmentation, multimodal integration, careful feature engineering, uncertainty quantification).\nGuide strategy for synthetic control arms and comparable approaches (as appropriate), ensuring methodological rigor, transparency, and fit-for-purpose use in decision-making.\nDrug Discovery / Translational Partnership\nTranslate drug discovery and translational questions into testable analytical hypotheses; partner with bench scientists to design data capture that enables strong modeling.\nServe as a bridge between scientific teams and data/engineering, ensuring solutions are scientifically credible and operationally adoptable.\nCross-functional Enablement + Platform Integration\nPartner with stakeholders across R&D, CMC, Clinical, Safety, and IT/Security to implement scalable data pipelines and AI-enabledworkflows.\nContribute 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).\nExternal Partner/Vendor Leadership\nLiaise with external partners to evaluate tools, define statements of work, and deliver solutions-while ensuring knowledge transfer and sustainable internal ownership. \nOperational Excellence\nImprove internal processes through automation and analytics, focusing on measurable impact (cycle time, error reduction, throughput, decision latency).\nEstablish practical governance for data quality, documentation, and fit-for-use standards aligned with the realities of biopharma environments (including where regulated practices apply).\nWhat Success Looks like (First 6-12 Months)\nA prioritized AI/analytics roadmap tied to measurable R&D outcomes; clear ownership and delivery cadence.\n2-4 production-grade analytics solutions adopted by teams (internal and/or external-facing outputs as needed).\nA repeatable approach for small datasets and high-noise signals; documented modeling standards and review practices.\nStrong partner engagement model: vendors/partners used strategically, with internal capability building and durable outcomes. \nRequired Skills and Qualifications\nAdvanced degree in a quantitative or scientific discipline (PhD strongly preferred; MS with exceptional experience considered).\n10+ 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.\nDeep familiarity with advanced ML methods (including XGBoost, Random Forest, SVMs) and the judgment to select and justify the right tool for the job.\nDemonstrated experience building predictive models with real-world, imperfect datasets and delivering them into production or decision workflows.\nProven ability to improve processes and operationalize analytics-moving beyond prototypes to adoption.\nStrong cross-functional communication: can partner with scientists, engineers, and executives; can explain model performance and limitations clearly.\nPreferred Skills and Qualifications\nDirect experience in drug discovery, translational research, and/or R&D decision support (target ID/validation, MoA, biomarker strategy, preclinical data integration).\nExperience with small data strategies, causality-aware thinking, and synthetic control arms or closely related methodologies.\nExperience operating in regulated/quality-sensitive environments and building documentation practices that scale (particularly relevant where validation and traceability are required).\nFamiliarity with enterprise data platforms and modern analytics stacks (lakehouse/warehouse patterns, feature stores, MLOps, model monitoring).","description_format":"text","description_chars":5954,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Pharmaceuticals","Drug Discovery","Health Care","Cell & Gene Therapy"],"lifecycle":[{"event":"open","at":"2026-09-12T01:59:28Z"}],"liveness":{"score":6,"band":"cold","label":"Long shot","p_open":1,"p_active":0.231,"p_room":0.28,"age_days":188,"expected_fill_days":43,"reasons":["conf:2","win:tail","crowd:"],"computed_at":"2026-09-24T05:45:00Z"},"pay":{"stated_usd_annual":332000,"is_top_pay":true},"html_url":"https://alion.io/job/lexeotx-senior-director-ai-and-data-science-drug-discovery-and-rd-enablement","json_url":"https://alion.io/job/lexeotx-senior-director-ai-and-data-science-drug-discovery-and-rd-enablement.json","meta":{"generated_at":"2026-09-24T17:48:15Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}