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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 approaches (e.g, full fine-tuning, parameter-efficient methods like LoRA, QLoRA)

• Retrieval-Augmented Generation (RAG) and knowledge integration

• Evaluation methods for generative models (e.g, perplexity, BLEU, ROUGE, human evaluation)

• Alignment techniques (e.g, RLHF, constitutional AI, red-teaming)

• Multimodal generative models (text-to-image, text-to-video, multimodal understanding)

• Responsible AI considerations specific to generative models (e.g, bias, hallucinations, safety)

• Familiarity with Gen AI frameworks and tools (e.g, Hugging Face and LangChain)

Machine Learning

• Classic ML algorithms (e.g, linear and logistic regression, decision and boosted trees, SVM, collaborative filtering, ranking)

• Approaches (e.g, supervised, semi-supervised, unsupervised, reinforcement learning, regression, classification, time series modeling, transfer learning)

• Foundational ML concepts such as objective functions, regularization and over fitting

• Data partitions (train/dev/test) and model development

• Hyperparameter tuning and grid search

• Evaluation concepts (metrics, feature importance, etc.)

• Familiarity with standard python packages (scikit-learn, XGBoost, TensorFlow, PyTorch, etc.)

• Familiarity with structure of machine learning pipelines

• Deep Learning (basic understanding expected at all levels)

• Activation functions

• Optimization/Gradient Decent

• Common architectures (CNN, RNN, LSTM, GAN, etc.)

• Embeddings

• Familiarity with specializations (sequence modeling/NLP/computer vision)

Math

• Linear Algebra

• Discrete math

• Probability and Statistics

• Calculus

Data

• Research and experiment design

• Visualization with data

• Answering questions with data

What You Will Do at Cambia (Not limited to):

Note that these responsibilities are representative but not exhaustive. Higher-level roles involve successively stronger degrees of initiative taking and innovation beyond the core responsibilities listed here.

• Researches, designs, develops, and implements data-driven models and algorithms using generative AI, machine learning, deep learning, statistical, and other statistical modeling techniques.

• Trains and tests models, and develops algorithms to solve business problems.

• Adheres to standard best-practices and establishes principled experimental frameworks for developing data-driven models.

• Develops models and performs experiments and analyses that are replicable by others.

• Uses open-source packages and managed services when appropriate to facilitate model development

• Identifies, measures, analyzes, and visualizes drivers to explain model performance (e.g, feature importance, interpretability, bias and error analysis), both offline (in the development phase) and online (in production).

• Uses appropriate metrics and quantified outcomes to drive AI model and algorithm improvements.

• Generates new features, by following examples, using SQL or SQL-like code.

• Works effectively with data that may be noisy, high dimensional, sparse and/or imbalanced.

• Contributes to the full life-cycle of modeling, from training or fine-tuning, to model evaluation, to model deployment.

• Builds robust production grade AI pipelines using tools and patterns in the AI platform.

• Accesses and processes structured and unstructured data in various databases and formats.

• Assesses new AI and ML capabilities and adapts them to our problems and environment.

• Identifies or develops appropriate model metrics and objective functions to ensure models satisfy stated business requirements and KPIs.

• Proactively identifies potential pitfalls and risks and develops ways to avoid them.

• Plays a role in ensuring that the work being carried out by the AI team has sufficient business value.

• Writes clean, well-commented, efficient Python code.

The expected hiring range for The AI Scientist II is $114k-$145k/year, 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 position is $114K - $186K/year.

About Cambia

Working at Cambia means being part of a purpose-driven, award-winning culture built on trust and innovation anchored in our 100+ year history. Our caring and supportive colleagues are some of the best and brightest in the industry, innovating together toward sustainable, person-focused health care. Whether we're helping members, lending a hand to a colleague or volunteering in our communities, our compassion, empathy and team spirit always shine through.

Why Join the Cambia Team?

At Cambia, you can:

• Work alongside diverse teams building cutting-edge solutions to transform health care.
• Earn a competitive salary and enjoy generous benefits while doing work that changes lives.
• Grow your career with a company committed to helping you succeed.
• Give back to your community by participating in Cambia-supported outreach programs.
• Connect with colleagues who share similar interests and backgrounds through our employee resource groups.

We believe a career at Cambia is more than just a paycheck - and your compensation should be too. Our compensation package includes competitive base pay as well as a market-leading 401(k) with a significant company match, bonus opportunities and more.

In exchange for helping members live healthy lives, we offer benefits that empower you to do the same. Just a few highlights include:

• Medical, dental and vision coverage for employees and their eligible family members, including mental health benefits.
• Annual employer contribution to a health savings account.
• Generous paid time off varying by role and tenure in addition to 10 company-paid holidays.
• Market-leading retirement plan including a company match on employee 401(k) contributions, with a potential discretionary contribution based on company performance (no vesting period).
• Up to 12 weeks of paid parental time off (eligibility requires 12 months of continuous service with Cambia immediately preceding leave).
• Award-winning wellness programs that reward you for participation.
• Employee Assistance Fund for those in need.
• Commute and parking benefits.

Learn more about our benefits.

We are happy to offer work from home options for most of our roles. To take advantage of this flexible option, we require employees to have a wired internet connection that is not satellite or cellular and internet service with a minimum upload speed of 5Mb and a minimum download speed of 10 Mb.

We are an Equal Opportunity employer dedicated to a drug and tobacco-free workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, age, sex, sexual orientation, gender identity, disability, protected veteran status or any other status protected by law. A background check is required.

If you need accommodation for any part of the application process because of a medical condition or disability, please email CambiaCareers@cambiahealth.com. Information about how Cambia Health Solutions collects, uses, and discloses information is available in our Privacy Policy.