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2 месяца назад

AVP, Machine Learning & Modeling

156 500 - 290 100$
Формат работы
onsite
Тип работы
fulltime
Грейд
head
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
AVP, Machine Learning & Modeling (Machine Learning/AI): Leading the design, development, and implementation of advanced analytics, statistical modeling, and artificial intelligence solutions across the enterprise with an accent on forecasting, risk assessment, operational efficiency, and client performance improvement. Focus on model governance and compliance, scalable ML deployment, emerging AI methodologies, and building high-performing multidisciplinary data science teams.

Location: Irving, Texas, United States — hirify.global Corporate HQ

Salary: $156,500–$290,100 per year, plus incentive eligibility

Company

hirify.global provides enterprise healthcare performance and analytics solutions.

What you will do

  • Set the strategic direction and roadmap for machine learning, modeling, predictive analytics, and optimization initiatives.
  • Oversee the design, development, validation, and deployment of statistical, econometric, and machine learning models.
  • Establish model governance, documentation, version control, validation, and ongoing performance monitoring.
  • Lead and mentor data scientists, ML engineers, quantitative analysts, and other multidisciplinary specialists.
  • Partner with business leaders, IT, risk management, compliance, and analytics stakeholders to deliver measurable business outcomes.
  • Evaluate emerging AI tools, frameworks, and methodologies to improve model performance and scalability.

Requirements

  • Bachelor’s, master’s, or doctoral degree in data science, statistics, computer science, applied mathematics, engineering, economics, or a related quantitative field preferred.
  • Expertise in machine learning, deep learning, statistical modeling, regression, time series, NLP, ensemble methods, and neural networks.
  • Strong proficiency in Python, SQL, and cloud-based AI/ML platforms such as AWS SageMaker, Azure ML, or Databricks.
  • Knowledge of MLOps, model governance, and model lifecycle management best practices.
  • Experience translating business problems into analytical frameworks and presenting complex findings to non-technical audiences.
  • Proven experience building and leading high-performing data science teams in a large, matrixed organization; familiarity with healthcare, financial, or operational analytics.

Culture & Benefits

  • Inclusive environment focused on employee engagement, authenticity, and meaningful contribution.
  • Extensive personal and professional development opportunities.
  • Comprehensive benefits plan.
  • Equal employment opportunity for all employees and applicants.

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