Sr. Data Scientist, Commercial Analytics

Sr. Data Scientist, Commercial Analytics at Cedar USA 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 patients' needs, identify improvement opportunities, and influence 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 patient experience. 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.

The Role:

We're seeking a Senior Data Scientist to join our Commercial Analytics team and lead the development of an internal agentic intelligence product— Cedar's next-generation analytics platform that transforms how health systems understand and optimize their revenue cycle operations. The Commercial Analytics team's goal is to enable our internal and external clients to understand, appreciate, and extract the maximum value from their Cedar relationships and products. The team's ambition is to satisfy and delight Cedar's clients through access to data and insights that: Help them build trust in Cedar's products and recognize the value they deliver Empower them to take advantage of Cedar's varying features and levers to maximize value Enable them to proactively identify and resolve revenue cycle issues before they become costly problems Today, health systems rely on static dashboards and manual analyst support to answer even routine questions about collection rates, payment plan defaults, and AR aging. We're building a platform that changes that — one where clients and internal teams can ask questions in natural language, receive instant answers with automated root cause analysis, and take action the same day. This role sits at the center of that build. As a Senior Data Scientist, you will be viewed as a force multiplier for your squad, displaying leadership and beginning to have an impact beyond your own tasks. You will lead squad-level projects, mentor junior team members, and drive decision-making within your team. You will develop deep expertise in Cedar's data ecosystem and Revenue Cycle Management domain, translating complex business problems into scalable analytics products that serve Cedar's client base.

Key Responsibilities:

Architect and build the decoupled semantic layer that powers RCM Intelligence — extracting metric definitions into a queryable format (MetricFlow/dbt Semantic Layer) that serves dashboards, natural language queries, and agentic systems from a single source of truth Design and develop metric frameworks and root cause analysis capabilities, including metric trees that decompose performance changes (e.g., why did metric X drop?) into their contributing factors — enabling clients and internal technical teams to self-serve answers that today require hours of analyst work Execute ambiguous, complex projects independently, proactively asking for help when needed, and translating client needs into structured analytical solutions Lead and execute sophisticated ad-hoc analyses using Python and SQL, then translate findings into scalable, parameterized data products that serve all clients rather than being rebuilt one-off Develop and optimize production data pipelines in dbt, ensuring consistent metric definitions and data quality across Cedar's Bronze → Silver → Gold architecture Serve as a thought partner to Technical Account Managers and Client Managers, using internal data products to surface proactive insights that strengthen client relationships and reduce reactive fire drills Partner with Data Engineers to implement robust infrastructure that supports the platform's analytical requirements and ensures scalability Present and communicate platform capabilities, analytical findings, and methodology to commercial stakeholders and clients — translating technical concepts for non-technical audiences Identify and advocate for opportunities to enhance Revenue Cycle Management Intelligence's impact, including features that reduce manual analyst work and increase client self-service

Skills and Experience:

5-7+ years of experience in analytical roles with demonstrated impact on business outcomes, preferably in healthcare, fintech, or B2B SaaS Deep proficiency in SQL and dbt, including production pipeline development and semantic layer modeling — experience with MetricFlow or dbt Semantic Layer a strong plus Experience building client-facing analytics products or BI tools, particularly those requiring parameterization across different client configurations Proficiency in Python for data analysis, notebook-based exploration, and analytical prototyping Ability to translate complex business problems and domain requirements into structured analytical approaches and scalable data products Strong presentation and communication skills, with the ability to influence decision-making and articulate technical concepts to diverse audiences Analytical ability and understanding of statistical methods for measuring business impact Experience decomposing ambiguous problems and executing solutions independently with a proactive, ownership-driven mindset Familiarity with NLP, agentic analytics, or LLM-powered BI tools (e.g., natural language querying, automated root cause analysis) is a plus Experience with modern agentic or AI-native BI platforms (e.g., Omni, Lightdash, Hex, or similar) in a production analytics environment is a plus Experience mentoring junior team members is a plus Knowledge of healthcare revenue cycle management — AR aging, payment plans, collections, patient financial experience — is a plus Experience with Snowflake or cloud data warehouse environments in a production setting is a plus Compensation Range and Benefits Salary/Hourly Rate Range•: $182,750 - $215,000 This role is equity eligible This role offers a competitive benefits and wellness package •Subject to location, experience, and education