At MCG, we lead the healthcare community to deliver patient-focused care. We have a mission-driven team of talented physicians and technical experts developing our evidence-based content and innovating our products to accelerate improvements in healthcare. If you are driven to enhance the US healthcare system, MCG is eager to have you join our team. We cultivate a work environment that nurtures personal and professional growth, and this is a thrilling time to become a part of our organization. With dynamic roles that offer meaningful impact, you'll be able to fully realize your potential. Plus, you'll enjoy world-class benefits and the security, stability, and resources of our parent company, Hearst, with over 100 years of experience.
MCG develops evidence based guidelines that help patients get the right care in a variety of healthcare settings. The data science team at MCG combines machine learning with the expert knowledge of our guidelines to increase the efficiency and accuracy of our users’ documentation workflows.
As Principal Data Scientist you will serve as the technical leader for our Natural Language Processing research and development, bringing NLP features from product request to experiment to production code. You will bring experience with best practice and lead brainstorming, technical design, prioritization of experiments, and managing dependencies. You will keep abreast of the state of the art in LLMs while guiding the team’s research of novel techniques to solve issues unique to our application.
You Will:
- Translate desired product functionality into machine learning tasks for data scientist and machine learning engineers to solve
- Lead and establish best practices for various research activities including data collection/annotation, literature research, experimentation, and evaluation
- Provide technical and project leadership for other Data Scientists
- Create and test novel LLM based systems
- Stay informed on new methodologies for evaluating generative models and other complex deep learning techniques
Our Tech Stack:
- Primarily Python jobs and applications
- OpenAI and other proprietary LLM APIs
- AzureML for Pytorch training
- Kubernetes via AKS or EKS for compute (with support from infra team)
- Databricks for data lake
- Flyte for orchestration
What We're Looking For:
- 8 years of experience in Data Science or Machine Learning Engineering
- Expert level Python: able to write reliable, extensible code
- Demonstrated experience translating high level requirements into models in production
- Deep experience with Natural Language Processing (NLP)
- Knowledge of deep learning fundamentals and experience finetuning various foundation/backbone models for new tasks
- Experience using pretrained LLM’s for zero or few-shot learning tasks
- Experience generating visualizations for evaluation of complex systems
- Scientific mindset and ability to run experiments to guide model selection and hyperparameter search
Preferred Qualifications:
- Good written communication skills
- Experience putting LLM based services into production
- Experience working with clinical data
- Experience with cloud-based machine learning training providers (Sagemaker, AzureML or similar)
Pay Range: $183,600– $257,000 yearly
Other compensation: Bonus Eligible
Perks & Benefits:
💻 Remote work
🩺 Medical, dental, vision, life, and disability insurance
📈 401K retirement plan; flexible spending and health savings account
🏝️ 15 days of paid time off + additional front-loaded personal days
🏖️ 14 company-recognized holidays + paid volunteer days
👶 up to 8 weeks of paid parental leave + 10 weeks of paid bonding leave
🌈 LGBTQ+ Health Services
🐶 Pet insurance
📣 Check out more of our benefits here: https://www.mcg.com/about/careers/benefits/
We embrace diversity and equal opportunity and are committed to building a team that represents a variety of backgrounds, perspectives, and skills. Only with diverse thoughts and ideas will we be able to create the change we want in healthcare. The more inclusive we are, the better our work will be for it.
MCG Health is a Seattle, Washington-based company and is considering remote candidates with a preference for those located in Seattle.
All roles at MCG are expected to engage in occasional travel to participate in team or company-sponsored events for the purposes of connection and collaboration.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
MCG is a leading healthcare organization dedicated to patient-focused care. We value our employees' unique differences and are an Equal Employment Opportunity (EEO) employer. Our diverse workforce helps us achieve our goal of providing the right care to everyone. We welcome all qualified applicants without regard to race, religion, nationality, gender, sexual orientation, gender identity, age, marital status, veteran status, disability, pregnancy, parental status, genetic information, or political affiliation. We are committed to improving equity in healthcare and believe that a diverse workplace fosters curiosity, innovation, and business success. We are happy to provide accommodations for individuals. Please let us know if you require any support.
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What We Do
MCG, part of the Hearst Health network, helps healthcare organizations implement informed care strategies that proactively and efficiently move patients toward health. MCG’s independent and transparent review of clinical evidence gives healthcare organizations confidence in their patient-centered care. By leveraging artificial intelligence and other technology, MCG presents this information within the workflow, to simplify and prioritize the work. MCG’s world-class customer service team ensures that clients are able to maximize the benefits of ownership for both content and software – demonstrating a return on financial investment as well as patient outcomes. Our solutions are used by several U.S. government agencies, a majority of U.S. health plans, and nearly 2,600 hospitals.
