[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 by 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 building testable pipelines, not just ad hoc analysis • 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. - Prior healthcare experience is a plus, but not required if you bring the aptitude and motivation • 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 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 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 tot his job