Gainwell Technologies - Austin, TX

posted 4 days ago

Full-time - Mid Level
Remote - Austin, TX
Professional, Scientific, and Technical Services

About the position

Gainwell Technologies is seeking an experienced Data Scientist to join the Payment Integrity Organization's Machine Learning and Generative AI team. This role focuses on developing and maintaining machine learning pipelines using modern ML approaches, with an emphasis on implementing practical solutions that enhance efficiency and drive revenue growth. The position offers opportunities for career development and emphasizes work flexibility, learning, and technical skill enhancement.

Responsibilities

  • Automate machine learning algorithms and develop end-to-end machine learning pipelines for production.
  • Formulate analytics solutions and evaluate strategies for ongoing improvement.
  • Implement scalable solutions for large data volumes while minimizing latency.
  • Ensure compliance with regulatory requirements and maintain high data security standards.
  • Create dashboards, reports, and data visualizations for ML prototyping and actionable insights.

Requirements

  • Minimum 5 years of professional experience in statistics, data science, analytics, or related roles.
  • Strong proficiency in Python and SQL, with experience using machine learning libraries such as scikit-learn, pandas, and numpy.
  • Experience with deep learning libraries based on Tensorflow and Pytorch.
  • Knowledge of foundational large language models including BERT and GPT.
  • Experience within healthcare data systems or payment integrity space and analytics is preferred.

Nice-to-haves

  • Knowledge of GPU architectures and experience using GPU clusters in AWS, Azure, or Google Cloud Platform.
  • Understanding of asynchronous, concurrent, and parallel processing.
  • Familiarity with machine learning platforms including Databricks.

Benefits

  • Generous flexible vacation policy
  • 401(k) employer match
  • Comprehensive health benefits
  • Educational assistance
  • Leadership and technical development academies
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