Machinify

5 months ago

Staff Data Scientist | Modeling

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Lead development of ML models for healthcare claims auditing, build scalable modeling infrastructure, and work with large, nuanced healthcare data pipelines to improve claim audits. Collaborate with clients and internal teams to translate model outcomes into actionable business insights, advancing our AI-powered platform in the healthcare payments domain.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Master Claim Audits: Dive into clinical and coding audits, unpacking the data that drives audit decisions and understanding past outcomes.
•Model Advancement: Curate labeled data, hypothesize new features, and develop ML models that target claims for audit with greater precision.
•Optimize Impact: Measure model performance rigorously, translating outcomes into operational insights and recommendations for clients.
•Tame Complexity: Work with vast, nuanced data pipelines from intricate business workflows—often unclean and undefined—to refine them for robust modeling.
•Drive Team Success: Enhance data pipelines, modeling infrastructure, and team tools to improve capabilities and decision-making efficiency.

Pay and Benefits

Equity and Bonus:Equity

Perks:Health InsuranceEquityPaid Leave401k

Key Requirements

•5+ years building ML models in Python, R, or similar languages with strong production deployment experience
•Proficiency in SQL and handling large-scale data pipelines
•Experience building ML models using Neural Nets or Tree-ensembles from scratch for new applications
•Ability to measure and optimize direct business impact of modeling work
•Healthcare data experience or domain knowledge related to health plans and claims auditing

Experience:5+ yearsHealthcare

Skills:Problem-solvingCommunicationCollaboration

Languages:English

Tech Stack:SQLPythonRNeural NetsTree-ensemblesMachine learning

Company Brief

Machinify

Industry: Industrial Automation

Website

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Machinify

5 months ago

Staff Data Scientist | Modeling

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Master Claim Audits: Dive into clinical and coding audits, unpacking the data that drives audit decisions and understanding past outcomes.
•Model Advancement: Curate labeled data, hypothesize new features, and develop ML models that target claims for audit with greater precision.
•Optimize Impact: Measure model performance rigorously, translating outcomes into operational insights and recommendations for clients.
•Tame Complexity: Work with vast, nuanced data pipelines from intricate business workflows—often unclean and undefined—to refine them for robust modeling.
•Drive Team Success: Enhance data pipelines, modeling infrastructure, and team tools to improve capabilities and decision-making efficiency.

Pay and Benefits

Equity and Bonus:Equity

Perks:Health InsuranceEquityPaid Leave401k

Key Requirements

•5+ years building ML models in Python, R, or similar languages with strong production deployment experience
•Proficiency in SQL and handling large-scale data pipelines
•Experience building ML models using Neural Nets or Tree-ensembles from scratch for new applications
•Ability to measure and optimize direct business impact of modeling work
•Healthcare data experience or domain knowledge related to health plans and claims auditing

Experience:5+ yearsHealthcare

Skills:Problem-solvingCommunicationCollaboration

Languages:English

Tech Stack:SQLPythonRNeural NetsTree-ensemblesMachine learning

Company Brief

Machinify

Industry: Industrial Automation

Website