Healthcare Data Scientist - SAS Programmer (remote US only)

Company Description

At ArborMetrix, advancing healthcare through data science is our mission, and delivering high impact, intuitive technology and analytics is our passion. Our leading healthcare intelligence solutions are proven to identify actionable insights that drive physician engagement, advance care, and improve patient outcomes, and our platform delivers clinically relevant and timely analytics and reports that have been shown to effectively target ways to improve healthcare quality and efficiency. We deliver clinically rich solutions that lead to results that have a real impact on real people.

Job Description

As a Data Scientist, you will work with our client services and product delivery teams to build data solutions to feed our healthcare performance-measurement and analytic web applications. These applications help our clients optimize the quality and cost-efficiency of hospital and specialty care.

We are looking for technical, organized, and strong communicators to facilitate product delivery for our clients. This includes all aspects of analytic projects including: designing analytic plans, dataset preparation, data quality validation, analytic programming, and the interpretation and communication of findings. We are looking for a strong data scientist with advanced SAS and SQL programming abilities, problem-solving, and excellent communication skills.

Our clients include hospitals and health systems, collaborative quality initiatives, and professional societies across various surgical specialties, health plans, and accountable care organizations.

Primary Responsibilities

• Manage and analyze large data sets including clinical registries, administrative data, billing claims, insurance and other data sets and statistical analysis
• Develop clear and well-structured analytic plans
• Create efficient and reusable code to manipulate and analyze data
• Build statistical models and diagnose, validate and improve the performance of the models
• Communicate effectively with internal and external stakeholders on analytic data processing

Qualifications

• Ability to assess technical challenges and program solutions, and solve complex problems
• Proven history working in a collaborative team environment and flexibility in taking on multiple projects
• Strong experience coding in data manipulation and analysis using SAS (required), SQL (required) and/or Python (preferred)
• Experience using SAS and SQL to process large, complex health insurance claims datasets
• Experience fitting and validating common statistical models (e.g., linear and logistic regression, GLMs) and interpreting model coefficients
• Experience working with servers and using the Linux command line, bash, or Windows Subsystem for Linux (WSL)
• Familiarity with Git and GitLab is preferred
• Experience with more advanced machine learning models (e.g., random forests, LLMs) is a plus
• Excellent written and oral communication skills
• Record of academic and/or business achievement
• Bachelor’s degree (Information, Operations Engineering, Statistics, Mathematics, IT, or Computer Science majors preferred)
• At least 2-3 years of analytic programming experience, preferably in healthcare

Additional Information

ArborMetrix has an outstanding entrepreneurial team with a strong mix of clinical analytics, software, and business expertise.

We value creativity, innovation, problem solving, collaboration, and fast iteration, which allows us to continuously improve our platform. 

This position is open to residents of the U.S. We are not currently accepting applicants in California, Colorado, New York, or Washington. The salary range for this role is $85,000-$100,000 USD annually.

ArborMetrix is an equal opportunity employer and does not discriminate in its selection and employment practices on the basis of race, color, religion, sex, national origin, political affiliation, sexual orientation, gender identity, marital status, disability, genetic information, age, membership in an employee organization, or other non-merit factors.

All your information will be kept confidential according to EEO guidelines.