Machinify · 2 hours ago
Data Scientist | Clinical AI
United States
Full-time
Remote
Mid LevelMachinify 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.
AnalyticsArtificial Intelligence (AI)Business IntelligenceMachine LearningPredictive AnalyticsSaaS
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
Qualification
Required
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
Preferred
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
Machinify
Machinify is a SaaS platform that enables non-technical enterprises to build AI-powered products and processes.
Founded in 2016
1001-5000 employees
H1B Sponsorship
Machinify has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (12)
2024 (6)
2023 (3)
2022 (3)
2021 (4)
2020 (5)
Funding
Current Stage
Late StageTotal Funding
$12.79MKey Investors
Battery Ventures
2025-01-10Acquired
2018-10-08Series A· $10M
2016-03-15Seed· $2.79M
Leadership Team
Edward Lichty
Strategic Operations
Prasanna Ganesan
EVP & Chief Product Officer
Recent News
2025-12-19
Dallas Morning News
2025-10-24
globallegalchronicle.com
2025-10-24
Company data provided by crunchbase