Machine Learning Engineer III

Our healthcare system is the leading cause of personal bankruptcy in the U.S. Every year, over 50 million Americans suffer adverse financial consequences as a result of seeking care, from lower credit scores to garnished wages. The challenge is only getting worse, as high deductible health plans are the fastest growing plan design in the U.S.

Cedar’s mission is to leverage data science, smart product design and personalization to make healthcare more affordable and accessible. Today, healthcare providers still engage with its consumers in a “one-size-fits-all” approach; and Cedar is excited to leverage consumer best practices to deliver a superior experience.

Background:

Cedar is a patient payment and engagement platform that leverages data science, consumer-centric design and technology to improve the healthcare experience for patients.

The Data Science team plays a critical role in achieving Cedar’s vision. We ensure data and insights are accessible and trusted by all internal and external stakeholders to enable data-driven decision-making. Through analytics, descriptive analyses, and statistical models, we consistently aim to better understand the needs of patients, find improvement opportunities, and impact the product development process. We run experiments to test our various hypotheses and measure our progress. We build ML models and embed them into our web app to deliver a personalized experience to patients. We help differentiate Cedar's product offerings with hard-to-copy competitive advantages.

To do this, we have built an open, supportive, and collaborative team culture. “Love thy teammate” is one of our Data Science values, and we live into this value by operating from a mindset of curiosity, possibility, and the best intentions of each of our team members. As a team, we are dedicated to continually growing our technical excellence and collaborative excellence, equally.

We are also not doing this alone; we partner with the other Makers teams (Product, Engineering, Design, and User Research) to grow our impact. We also work with Commercial teams to evangelize our vision to clients and get market feedback on which pain points are the most urgent to solve.

You can read about some of our work on the Patient Experience Studio, a blog we share with the Design team.

The Role:

Cedar is scaling rapidly and the demand for data and machine learning expertise is increasing. We are seeking a Machine Learning Engineer III to join our team and build machine learning solutions that optimize the performance of Cedar’s product. You will conduct deep analyses of data to develop a thorough understanding of our product features and how patients utilize them, along the way becoming an expert in Cedar data. You will design, develop, and iterate on ML-powered product features to support and differentiate Cedar’s product offerings, and closely measure and monitor the performance of these ML models to identify and drive opportunities for continuous improvement. As Cedar’s ML capabilities evolve, you will have the opportunity to expand your scope and influence key decisions about how ML is utilized in Cedar’s products. 

Responsibilities:

• Develop a deep understanding of Cedar patients and our product, including the mechanisms of Cedar’s platform and Cedar’s data
• Build and optimize pipelines for data extraction, processing, and transformation; perform in-depth data analysis, data cleaning, and feature engineering on (mostly) structured, tabular data 
• Design, build, and deploy scalable and maintainable machine learning solutions that solve key problems for our patients and customers
• Rigorously evaluate the effectiveness of machine learning models by analyzing their performance, and identify opportunities for iteration and improvement
• Collaborate closely with data engineers and product engineers to productionize pipelines and ML solutions
• Present and clearly communicate findings and underlying methodology to partners across all levels of the organization, and present externally to Cedar clients
• Work cross-functionally to identify and evaluate opportunities where machine learning can drive business impact and competitive advantage
• Take ownership of end-to-end machine learning projects, from ideation to deployment, with increasing autonomy as you grow in the role

Skills and Experience:

• 5+ years of experience working with data, with 3+ years of experience in machine learning in an industry setting
• Expertise in both SQL and Python is required
• Expertise in machine learning techniques such as regression, classification, clustering, and ensemble methods; not only in training performant mo