[Remote] Data Scientist | Clinical AI
Note: The job is a remote job and is open to candidates in USA. Machinify is a leading healthcare intelligence company focused on delivering value and efficiency to health plan clients. They are seeking a Data Scientist to advance their AI system for clinical criteria evaluation, translating medical policies into executable logic and building robust clinical feature pipelines.
Responsibilities
• Translate medical policy into executable logic - Read and interpret medical policies and clinical criteria (e.g., lab thresholds, temporal windows, trend logic, exclusions)
• Convert requirements into correct, maintainable SQL and Python implementations (e.g., creatinine-based AKI rules, bilirubin thresholds, troponin dynamics, ABG-derived criteria)
• Design rule representations that are composable and auditable (clear inputs, outputs, assumptions, edge cases)
• Prompt engineering and system parameter tuning for AI configuration that extracts clinical information from medical records
• Build robust clinical feature pipelines
• Create and maintain pipelines that compute clinical features from extracted signals (labs, vitals, flowsheets, notes-derived facts)
• Handle tricky realities: missing timestamps, multiple measurement sources, unit normalization, deduplication, conflicting values, provenance tracking
• Own measurement, evaluation, and continuous quality improvement
• Define and instrument accuracy metrics for the AI system that extracts data from medical records
• Build gold datasets, sampling strategies, and review workflows with clinical/operations partners
• Perform error analysis, identify root causes (retrieval failures, OCR issues, extraction ambiguity, policy interpretation gaps), and drive improvements
• Establish engineering frameworks and tooling
• Create reusable tooling for policy-to-code translation: templates, test harnesses, validation suites, regression checks, and monitoring dashboards
• Improve infrastructure for large-scale runs: orchestration, logging, lineage, versioning, and reproducibility
• Implement guardrails and QA gates so policy logic changes are safe, traceable, and measurable
• Partner deeply with domain experts
• Work with clinicians, policy specialists, and operations to clarify ambiguous requirements and ensure implementations reflect real-world intent
• Produce clear documentation that explains what the code is doing and why, with examples and edge-case handling
Skills
• Strong SQL and Python engineering skills - Ability to translate nuanced requirements into correct SQL (CTEs, window functions, joins at scale, performance tuning) and production-quality Python
• Experience operationalizing rules + models - Track record of implementing complex business/clinical logic and deploying it reliably
• Comfort working with imperfect, messy, high-volume datasets
• Evaluation/Metric mindset - Experience designing metrics, building ground truth, running experiments, and improving system quality through structured iteration
• Ability to connect technical quality measures to business outcomes (e.g., accuracy vs reviewer burden vs downstream decisions)
• Systems thinking and rigor - You build frameworks that make other engineers/scientists faster: shared libraries, patterns, tooling, and clear interfaces
• You sweat details: edge cases, provenance, temporal logic, unit conversions, and regression safety
• Healthcare curiosity (and willingness to learn fast) - Interest in medical records, clinical data, and how policies translate into decision criteria
• Experience with clinical data standards or lab data normalization (LOINC familiarity, units conversion, reference ranges)
• Experience evaluating LLM/IE systems (information extraction) or building human-in-the-loop QA workflows
• Familiarity with distributed data systems (Spark, BigQuery/Snowflake, Databricks) and workflow orchestrators
Benefits
• Top Medical/Dental/Vision offerings
• FSA/HSA
• Tuition reimbursement
• Competitive salary, 401(k) with company match
• Unlimited PTO
• Additional health and wellness benefits and perks
Company Overview
• Machinify is a SaaS platform that enables non-technical enterprises to build AI-powered products and processes. It was founded in 2016, and is headquartered in Palo Alto, California, USA, with a workforce of 1001-5000 employees. Its website is http://www.machinify.com.
Company H1B Sponsorship
• Machinify has a track record of offering H1B sponsorships, with 12 in 2025, 6 in 2024, 3 in 2023, 3 in 2022, 4 in 2021, 5 in 2020. Please note that this does not guarantee sponsorship for this specific role.
Apply Now
Apply Now
Responsibilities
• Translate medical policy into executable logic - Read and interpret medical policies and clinical criteria (e.g., lab thresholds, temporal windows, trend logic, exclusions)
• Convert requirements into correct, maintainable SQL and Python implementations (e.g., creatinine-based AKI rules, bilirubin thresholds, troponin dynamics, ABG-derived criteria)
• Design rule representations that are composable and auditable (clear inputs, outputs, assumptions, edge cases)
• Prompt engineering and system parameter tuning for AI configuration that extracts clinical information from medical records
• Build robust clinical feature pipelines
• Create and maintain pipelines that compute clinical features from extracted signals (labs, vitals, flowsheets, notes-derived facts)
• Handle tricky realities: missing timestamps, multiple measurement sources, unit normalization, deduplication, conflicting values, provenance tracking
• Own measurement, evaluation, and continuous quality improvement
• Define and instrument accuracy metrics for the AI system that extracts data from medical records
• Build gold datasets, sampling strategies, and review workflows with clinical/operations partners
• Perform error analysis, identify root causes (retrieval failures, OCR issues, extraction ambiguity, policy interpretation gaps), and drive improvements
• Establish engineering frameworks and tooling
• Create reusable tooling for policy-to-code translation: templates, test harnesses, validation suites, regression checks, and monitoring dashboards
• Improve infrastructure for large-scale runs: orchestration, logging, lineage, versioning, and reproducibility
• Implement guardrails and QA gates so policy logic changes are safe, traceable, and measurable
• Partner deeply with domain experts
• Work with clinicians, policy specialists, and operations to clarify ambiguous requirements and ensure implementations reflect real-world intent
• Produce clear documentation that explains what the code is doing and why, with examples and edge-case handling
Skills
• Strong SQL and Python engineering skills - Ability to translate nuanced requirements into correct SQL (CTEs, window functions, joins at scale, performance tuning) and production-quality Python
• Experience operationalizing rules + models - Track record of implementing complex business/clinical logic and deploying it reliably
• Comfort working with imperfect, messy, high-volume datasets
• Evaluation/Metric mindset - Experience designing metrics, building ground truth, running experiments, and improving system quality through structured iteration
• Ability to connect technical quality measures to business outcomes (e.g., accuracy vs reviewer burden vs downstream decisions)
• Systems thinking and rigor - You build frameworks that make other engineers/scientists faster: shared libraries, patterns, tooling, and clear interfaces
• You sweat details: edge cases, provenance, temporal logic, unit conversions, and regression safety
• Healthcare curiosity (and willingness to learn fast) - Interest in medical records, clinical data, and how policies translate into decision criteria
• Experience with clinical data standards or lab data normalization (LOINC familiarity, units conversion, reference ranges)
• Experience evaluating LLM/IE systems (information extraction) or building human-in-the-loop QA workflows
• Familiarity with distributed data systems (Spark, BigQuery/Snowflake, Databricks) and workflow orchestrators
Benefits
• Top Medical/Dental/Vision offerings
• FSA/HSA
• Tuition reimbursement
• Competitive salary, 401(k) with company match
• Unlimited PTO
• Additional health and wellness benefits and perks
Company Overview
• Machinify is a SaaS platform that enables non-technical enterprises to build AI-powered products and processes. It was founded in 2016, and is headquartered in Palo Alto, California, USA, with a workforce of 1001-5000 employees. Its website is http://www.machinify.com.
Company H1B Sponsorship
• Machinify has a track record of offering H1B sponsorships, with 12 in 2025, 6 in 2024, 3 in 2023, 3 in 2022, 4 in 2021, 5 in 2020. Please note that this does not guarantee sponsorship for this specific role.
Apply Now
Apply Now