AI Scientist II; Healthcare

AI Scientist II (Healthcare)

Hybrid (Office 3 days/wk - Onsite-Flex) within Oregon, Washington, Idaho or Utah

Build a career with purpose. Join our Cause to create a person-focused and economically sustainable health care system.

Who We Are Looking For:

Every day, Cambia's Applied AI Team is living our mission to make health care easier and lives better. AI Scientists work with various stakeholders to design, develop, and implement data-driven solutions. This position applies expertise in advanced analytical tools such as generative AI, machine learning, deep learning, optimization, and statistical modeling to solve business problems in the healthcare payer domain. AI Scientists work may focus on a particular area of the business such as clinical care delivery, customer experience, or payment integrity, or they may work across several areas spanning the organization.

In addition to expertise in generative AI, machine learning, deep learning and analytics this role requires knowledge of data systems, basic software development best practices, and algorithm design.

AI Scientists work closely with AI team members in the Product and Engineering tracks to collaboratively develop and deliver models and data-driven products. AI Scientists also collaborate and communicate with business partners to design and develop data-driven solutions to business problems and interpret and communicate results to technical and non-technical audiences - all in service of making our members' health journeys easier.

If you're a motivated and experienced AI Scientist looking to make a difference in the healthcare industry, apply for this exciting opportunity today!

What You Bring to Cambia:

Qualifications and

Certifications:

* The AI Scientist II would have a degree (master's or PhD preferred) in a strongly quantitative field such as Computer Science, Statistics, Applied Mathematics, Physics, Operations Research, Bioinformatics, or Econometrics

* 4 years of related work experience

* Equivalent combination of education and experience

Skills and Attributes (Not limited to):

* Demonstrated knowledge of generative AI, machine learning and data science.

* Ability to use well-understood techniques and existing patterns to build, analyze, deploy, and maintain models.

* Effective in time and task management.

* Able to develop productive working relationships with colleagues and business partners.

* Strong interest in the healthcare industry.

* Ability to code effectively in and create novel features and datasets using SQL or SQL-like languages.

* Ability to write clean, well-commented, efficient Python code.

* Strong understanding of techniques for working with noisy, high-dimensional, sparse, and/or imbalanced data.

* Demonstrates in-depth familiarity with at least one domain of data (e.g, claims data).

* Demonstrates depth of understanding in at least one major AI modeling technique or approach.

* Ability to develop new AI pipelines for both offline testing and online serving of models.

* Demonstrated track record of delivery of AI and machine learning models to solve well-defined business problems.

* Has working knowledge of department processes, procedures, and infrastructure.

* Able to identify common pitfalls in developing AI and ML models (e.g, data leakage across features or partitions)

* Ability to translate business requirements into data science and AI discovery plans and modeling objectives.

* Ability to articulate the high-level business objectives of their work.

* Performs a range of data science tasks with a moderate level of guidance and direction.

* Ability to partner within and across departments to remove blocks and achieve results.

Core Knowledge:

* Generative AI:
Understanding of foundation models, transformer architectures, and techniques for working with large language models (LLMs).

Experience with prompt engineering, fine-tuning approaches, and evaluation methods for generative models.

* Machine Learning:
Strong mathematical foundation and theoretical grasp of the concepts underlying machine learning, optimization, etc. (see below). Demonstrated understanding of how to structure simple machine learning pipelines (e.g, has prepared datasets, trained and tested models end-to-end).

* Data:
Strong foundation in data analysis.

* Programming:
Strong python programming skills. Familiarity with standard data science packages. Familiarity with standard software development best practices. Strong SQL skills a plus.

* Algorithms:
Understanding of standard algorithms and data structures (ex. search and sort) and their analysis.

* Core Knowledge Details and Examples (meant to be representative, not exhaustive; entry level roles are expected to have hands-on experience training and testing AI models, solid mathematical understanding and computer science fundamentals)

Generative AI

* Large Language Models (LLMs) and their capabilities (e.g, in-context learning, few-shot learning, zero-shot learning)

* Prompt engineering techniques and best practices

* Fine-tuning…