AI Data Engineer

AI Data EngineerAlzheon, Inc. is a clinical-stage biopharmaceutical company developing a broad portfolio of product candidates and diagnostic assays for patients suffering from Alzheimer's disease and other neurodegenerative disorders. We are committed to developing innovative medicines by directly addressing the underlying pathology of devastating neurodegenerative disorders. Our lead Alzheimer's clinical candidate, ALZ-801, is an oral agent in Phase 3 development as a potentially disease modifying treatment for AD. ALZ-801 is an oral small molecule that fully blocks formation of neurotoxic soluble amyloid oligomers in the brain. Our clinical expertise and technology platform are focused on developing drug candidates and diagnostic assays using a precision medicine approach based on individual genetic and biomarker information to advance therapies with the greatest impact for patients.Our experienced and passionate drug development team is focused on applying precision medicine, cutting-edge disease biomarkers, brain imaging and unique biologic insights to advance therapies with the greatest impact for patients. We are seeking individuals with an entrepreneurial spirit to join our team and help make the first oral Alzheimer's disease-modifying therapy a reality for patients and their families, in a few short years.Position OverviewAlzheon is seeking a highly skilled and motivated AI Data Engineer to join our growing data science team. This role will be instrumental in building advanced AI models to understand and predict Alzheimer's disease progression using multimodal real-world and clinical trial data. The ideal candidate will have a strong background in data engineering, machine learning, and biomedical data, with a passion for transforming complex datasets into actionable insights that drive therapeutic innovation.Key ResponsibilitiesDesign, build, and maintain scalable data pipelines for ingesting, cleaning, and transforming multimodal datasets, including: clinical outcomes, fluid biomarkers, MRI imaging endpoints, real-world data (RWD)Develop and validate AI/ML models to characterize disease progression and treatment response across placebo and active treatment armsIntegrate diverse data sources to build comprehensive patient-level models of Alzheimer's diseaseCollaborate with clinical, biomarker, and imaging teams to align modeling efforts with scientific and clinical objectivesEnsure data quality, consistency, and compliance with regulatory standardsDocument and communicate model assumptions, performance, and limitations to technical and non-technical stakeholdersContribute to the development of internal data platforms and tools to support analytics and decision-makingStay current with advances in AI, machine learning, and neurodegenerative disease researchRequirementsMaster's or PhD in Computer Science, Data Science, Biomedical Engineering, or a related field5+ years of experience in data engineering and machine learning, preferably in the life sciences or healthcare domainProficiency in Python, SQL, and data pipeline frameworksExperience working with multimodal biomedical data, including imaging, omics, and clinical trial dataStrong understanding of statistical modeling, machine learning, and deep learning techniquesFamiliarity with cloud platforms (e.g., AWS, GCP) and containerization (e.g., Docker, Kubernetes)Excellent problem-solving skills and ability to work in a fast-paced, collaborative environmentStrong communication skills and ability to translate complex technical concepts to diverse audiencesPreferred QualificationsExperience with neuroimaging data (e.g., MRI, PET) and tools (e.g., FSL, FreeSurfer)Knowledge of Alzheimer's disease biology and clinical endpointsPrior experience in biotech or pharmaceutical R&DFamiliarity with CDISC standards (ADaM/SDTM)All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.