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    Senior Machine Learning Scientist - Boise, United States - Cambia Health

    Cambia Health
    Cambia Health Boise, United States

    4 weeks ago

    Default job background
    Description
    This job was posted by : For more information, please see: Senior Machine Learning Scientist

    Remote within OR, WA, ID or UT

    Cambia Health Solutions is working to create a seamless and frictionless healthcare experience for consumers nationwide.

    This presents a unique challenge and opportunity for innovative solutions that serve patients and providers and influence the healthcare system.

    Cambia\'s Applied AI team builds, prototypes, and deploys data-driven models and algorithms to production systems, delivering more equitable, effective, and affordable health care to our members.


    We are seeking a highly-skilled and experienced Senior Machine Learning Scientist to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better health care.

    We contribute broadly across Cambia, working on a wide range of challenging problems. In this role, we are seeking a technical leader for our Healthcare Services Operations AI team working on use cases such as

    Streamline prior authorization and appeal reviews using GenAI and NLP.

    Summarizing medical policy decisions in plain language for our members.

    Identifying members at risk for certain conditions to offer them opportunities for high-value care.

    And much more


    As a Senior ML Scientist on our team, you will play a crucial role in leading the team in understanding requirements, prototyping and building models, conducting experiments, and driving innovative solutions.

    Your passion for machine learning, deep learning, and NLP, coupled with your curiosity and desire to keep learning, will be instrumental in advancing Cambia\'s data-driven initiatives.

    In collaboration with your fellow ML Scientists, our AI product team, and our partner data engineering and software development teams, you will bring ML models to production and maintain their health and integrity while in production.

    Your expertise in theoretical machine learning, coupled with your practical experience engineering ML systems, will be instrumental in driving the success of Cambia\'s AI/ML initiatives.

    Qualifications and Requirements

    Academic degree (masters or PhD preferred) in Computer Science, Engineering, or a related field.

    Minimum of 7 years of experience in ML development and deploying ML solutions in cloud-based production environments for a Senior MLS I

    Minimum of 9-12 years of experience in ML development and deploying ML solutions in cloud-based production environments for a Senior MLS II

    Machine learning:

    Strong mathematical foundation and understanding of the concepts underlying classic machine learning, deep learning, NLP, statistical modeling, and data analysis.

    Expert-level familiarity with common machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, XGBoost, etc.

    Natural Language Processing (NLP): Expertise in NLP and experience using NLP libraries like NLTK, SpaCy, Gensim, etc. is a strong plus.


    Generative AI and Large Language models (strongly preferred): Understanding and experience working with language (LLM) models and generative AI, including encoder-only (BERT Family) and autoregressive models (GPT family).

    Experience using different frameworks and libraries including but not limited to huggingface, Langchain, Llamaindex, vector databases.

    Model development and evaluation:
    Experience in and deep intuition for applying ML techniques and approaches to solve problems. Strong foundation in model evaluation, including metric development and selection.

    Software development skills:
    Solid understanding of software engineering principles, data structures, and algorithms. Expert-level proficiency in Python.

    ML production systems:
    Experience deploying ML models in production systems. Exposure to containerization technologies (e.g., Docker, Kubernetes) and cloud pla forms (e.g., AWS, Azure, GCP) is helpful. Strong grounding in model monitoring and MLOps.

    Data preprocessing and analysis:
    Understanding of how to structure machine learning pipelines. Familiarity with data preprocessing techniques and tools. Experience with SQL and/or python data processing libraries (e.g., Pandas, NumPy).

    Analytical mindset:
    Strong analytical thinking and problem-solving abilities to contribute to data analysis and experimental evaluations. Attention to detail and an eagerness to learn from experimental results.

    Communication and teamwork:
    Good communication skills to collaborate effectively with cross-functional teams. Willingness to collaborate and learn with team members.

    Continuous learning:
    Passion for staying up-to-date with the latest advancements in machine learning and data engineering. Proactive in learning new tools, techniques, and frameworks to drive innovation.

    Leadership:
    Strong leadership, coaching, and mentorship abilities. Ability to inspire and motivate team members towards achieving goals and delivering high-quality results.

    Responsible AI:
    Desire to adhere to ethical considerations and responsible AI practices in machi
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