Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Средняяразвернуть
$190к-210к/год
$170к$200кмедиана$220к
По похожим ролям (50) ~ $200к/год
На СНГ рынке: $4.4к/мес ($3.8к - $6к)
89
Крутая вакансия
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Понятная ответственность за весь цикл ML, работа с продакшеном и финансируемый AI-продукт в здравоохранении делают это сильной вакансией для senior-уровня; при этом в задачи также входит часть работы с пайплайнами.
?Есть задачи по пайплайнам
Современный ML-стек
AI в здравоохранении
Серьёзное финансирование
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Data Scientist (AI): Building and deploying machine learning models for healthcare claims analytics and intelligence features with an accent on exploratory analysis, production integration, and model monitoring. Focus on developing data pipelines, applying MLOps and experiment tracking, and communicating findings across engineering, product, and customer-facing teams.
Location: New York City, United States; hybrid work
Base salary: $190,000–$210,000 per year, plus equity and bonus.
Company
hirify.global provides an AI orchestration platform for healthcare revenue cycle management, using automation, data science, and AI agents to improve revenue operations.
What you will do
Build and deploy machine learning models powering analytics and intelligence features.
Perform exploratory analysis on large-scale claims datasets to identify patterns and anomalies.
Collaborate with engineering to integrate models and data products into production systems.
Monitor model performance and iterate based on results.
Communicate findings to technical and non-technical stakeholders, including product and customer-facing teams.
Contribute to data pipeline and warehouse development as needed.
Requirements
4+ years of experience in data science or applied machine learning, including experience taking at least one model from development to production in a real product environment.
Strong proficiency in Python and SQL.
Solid grounding in statistics, probability, and machine learning fundamentals.
Hands-on experience with scikit-learn, XGBoost, or similar machine learning frameworks.
Experience with cloud infrastructure, preferably AWS.
Experience with data pipeline tooling and orchestration, such as sqlMesh, Temporal, or equivalent.
Ability to communicate findings clearly to technical and non-technical audiences.
Experience with MLOps tooling, including experiment tracking such as MLflow, orchestration such as Temporal or Prefect, and model monitoring.
Nice to have
Exposure to EHR or RCM data.
Familiarity with anomaly detection methods.
Familiarity with recommendation systems.
Culture & Benefits
Hybrid work in the New York City office.
Competitive equity package and employer-paid medical, dental, and vision insurance.
Employer-funded HSA, parental leave, commuter benefits, generous PTO, and daily office lunches and snacks.
Inclusive, equal-opportunity workplace with accessibility support under the ADA.
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