Machine Learning Scientist II

Machine Learning Scientist II

Remote or Hybrid or On-site within OR, WA, ID or UT

Apply below after reading through all the details and supporting information regarding this job opportunity.

Job Description :

Cambia Health Solutions is working to create a seamless and frictionless health care 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 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 talented and skilled Machine Learning Scientist II 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, for instance :

• 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 Machine Learning Scientist II, you will play a vital role 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 eagerness to learn and grow, will be instrumental in advancing Cambia’s data-driven initiatives.

Qualifications & Requirements :

Degree (masters or PhD preferred) in a strongly quantitative field such as Computer Science, Statistics, Applied Mathematics, Physics, Operations Research, Bioinformatics, or Econometrics, and typically requires 4 years of related work experience.

Equivalent combination of education and experience will be considered.

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

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

• Expertise in NLP and experience using LLM and NLP libraries like NLTK, spaCy, or Hugging Face transformers is a plus.
• Experience applying a variety of ML techniques and approaches to solve problems. Strong foundation in model evaluation, including metric development and selection.
• Basic understanding of software engineering principles and considerations for deploying ML models in production systems.

Exposure to containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, Azure, GCP) is helpful.

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).

• 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.
• Good communication skills to collaborate effectively with cross-functional teams. Willingness to collaborate and learn with team members.
• Previous healthcare experience is beneficial but not required.

Responsibilities :

• Use machine learning, deep learning, and NLP to prototype, develop, and refine models on top of our ML platform, leveraging best practices and established frameworks.
• Conduct experiments and evaluations to assess the performance and effectiveness of different models and techniques. Develop metrics that reflect the needs of the business for their use cases.
• Work with ML Engineers to optimize and adapt models for real-time, scalable, and efficient performance. Collaborate with engineering and infrastructure teams to ensure seamless integration and deployment of models into production systems.
• Collaborate with cross-functional teams to understand business requirements, define clear objectives, and develop technical plans.
• Implement robust and reusable data preprocessing and feature engineering pipelines to extract meaningful insights from raw data.
• Stay updated with the latest advancements in machine learning, deep learning, and NLP, particularly as applied in healthcare.

Work Environment :

Work primarily performed in an office environment and working from home may be considered. Travel may be required, locally or out of state.

May be required to work overtime and outside of normal hours.

The expected hiring range for a Machine Learning Scientist II is $119,900 - $162,200 depending on skills, experience, education, and training;

relevant licensure / certifications; performance history; and work location. The bonus target for this position is 15%. The current full salary range for this role is $112,000 - $184,000.

Base pay is just part of the compensation package at Cambia that is supplemented with an exceptional 401(k) match, bonus opportunity and other benefits.

We are an Equal Opportunity and Affirmative Action employer dedicated to workforce diversity and a drug and tobacco-free workplace.

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