{"id":1250281,"url":"https://alion.io/job/synapxe-senior-systems-analyst-ai-models-solutions-ngemr","title":"Senior Systems Analyst - AI models & Solutions (NGEMR)","company":{"id":1834356,"name":"Synapxe","domain":"synapxe.sg","url":"https://alion.io/company/synapxe","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":54000,"max_usd":103000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":49},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"closed","first_seen_at":"2026-09-22T00:00:00Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-10-31T19:54:13Z","board_verified":false,"closed_at":"2026-10-31T19:54:13Z","days_open":39,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":39},"description":"Position Overview\nThe Epic Nebula AI / Machine Learning Engineers design, deploy, integrate, and support artificial intelligence and machine learning solutions within the Epic ecosystem, working closely with clinicians, operational stakeholders, data scientists, Epic application teams, integration teams, security teams, and infrastructure teams to translate business and clinical requirements into safe, reliable, and scalable AI-enabled workflows; responsibility includes deploying predictive or machine learning models through Epic Nebula and the Epic Cognitive Computing framework, integrating model inputs and outputs into Epic workflows, and ensuring that deployed models meet organizational requirements for performance, security, privacy, explainability, clinical safety, and ongoing monitoring, a role that requires both technical expertise in machine learning engineering and a strong understanding of healthcare workflows, Epic applications, clinical data, and production support processes.\nRole & Responsibilities\nMeeting with clinicians, business stakeholders, Epic application analysts, data scientists, and subject matter experts to understand AI and predictive analytics requirements\nEvaluating whether proposed use cases are suitable for machine learning, generative AI, rules-based logic, or existing Epic functionality\nTranslating clinical and operational requirements into technical model-integration specifications\nPreparing, validating, and transforming Epic clinical and operational data for model development and inference\nDeploying internally developed or third-party predictive models through Epic Nebula and the Epic Cognitive Computing framework\nDeveloping and maintaining model input mappings, output mappings, configuration, APIs, and workflow integration components\nIntegrating model predictions, risk scores, classifications, recommendations, or generated content into appropriate Epic workflows\nWorking with Epic application teams to configure user-facing components such as alerts, decision-support activities, work queues, patient lists, dashboards, or other workflow touchpoints\nCollaborating with data scientists to package models and ensure that model artifacts meet Epic deployment requirements\nValidating model compatibility, dependencies, input schemas, output schemas, and runtime requirements\nPerforming unit testing, integration testing, workflow testing, performance testing, regression testing, and user acceptance testing\nAssessing model accuracy, calibration, sensitivity, specificity, false-positive rates, false-negative rates, fairness, and operational impact\nEstablishing monitoring for model availability, latency, data quality, prediction distribution, model drift, and workflow adoption\nInvestigating production issues involving model execution, data availability, interfaces, workflow configuration, or prediction delivery\nMaintaining model versioning, deployment records, technical documentation, validation evidence, and change-control documentation\nSupporting model promotion across development, test, validation, and production environments\nParticipating in Epic upgrades and reviewing changes that may affect Nebula, cognitive computing, data structures, interfaces, or embedded AI workflows\nEnsuring compliance with organizational policies relating to cybersecurity, patient privacy, clinical safety, responsible AI, and data governance\nSupporting periodic model review, recalibration, retraining, rollback, retirement, and replacement\nProviding technical guidance and knowledge transfer to Epic analysts, data scientists, application support teams, and operational users\nThe position shall also be responsible for:\nExternal models integrated with Epic\nReal-time and batch inference workflows\nGenerative AI and large language model integrations\nEpic Cognitive Computing configuration\nEpic Nebula model deployment and administration\nModel monitoring dashboards\nFeature engineering and reusable feature pipelines\nIntegration with Clarity, Caboodle, Chronicles, Cosmos, FHIR, or other approved clinical data sources\nIntegration with cloud-based AI or machine learning services\nClinical decision-support configuration\nAI governance and model inventory management\nEvaluation of third-party healthcare AI products\nRequirements\nA degree in computer science, data science, artificial intelligence, engineering, statistics, information systems, biomedical informatics, or a related discipline\nStrong programming skills in Python or another language commonly used for machine learning development\nProficiency with SQL and relational database concepts\nPractical understanding of machine learning development, validation, deployment, and monitoring\nExperience working with model-serving APIs, JSON, RESTful services, authentication, and system integration\nKnowledge of software development lifecycle, version control, automated testing, release management, and production support\nUnderstanding of model performance measures such as precision, recall, sensitivity, specificity, calibration, and area under the curve\nAbility to identify data leakage, bias, model drift, unstable features, and inappropriate model use\nStrong analytical, troubleshooting, and problem-solving skills\nStrong written and verbal communication skills\nAbility to explain technical model behaviour and limitations to clinical and non-technical stakeholders\nAbility to understand complex healthcare workflows and translate them into technical requirements\nAbility to work effectively across clinical, operational, data, application, infrastructure, cybersecurity, and governance teams\nUnderstanding of healthcare data privacy, security, clinical safety, and responsible-AI principles\nAbility to maintain accurate technical, validation, deployment, and operational documentation\nPreferred Epic-related competencies\nFamiliarity with Epic applications, workflows, and data structures\nFamiliarity with Epic Cognitive Computing, Nebula, or model deployment within Epic is strongly preferred\nExperience with Epic Clarity, Caboodle, Chronicles, or Cogito is an advantage\nExperience with Epic integration technologies, APIs, or FHIR is an advantage\nAbility to understand how model outputs affect clinician and operational workflows\nExperience supporting Epic upgrades, testing cycles, change control, and production releases is desirable\nEpic certification or proficiency in an applicable module is advantageous\nCertification or experience in Clarity Data Model, Caboodle Data Model, Cogito, Cognitive Computing, or relevant clinical applications is a significant advantage\nApply Now\nNOTE: It only takes a few minutes to apply for a meaningful career in HealthTech - GO FOR IT!!","description_format":"text","description_chars":6692,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Information 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