Data Scientist

About This Position

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse "big data" sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.

Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.

Incumbents whose primary role is technical and focused on data storage, warehousing and systems architecture should be matched to Database Engineering or Storage Engineering. Incumbents whose focus is the quantitative analysis of complex business problems and issues using data from internal and external sources to provide insight to decision-makers should be matched to Business Intelligence. Incumbents whose primary role is technical and focused on designing and building system-generated reports, reporting tools and dashboards for data generation should be matched to Data Informatics.

Incumbents whose focus is primarily on experimental design and advanced or complex statistical analysis and modeling of datasets should be matched to Statistician/Mathematician. This is a product engineering role in which employees work with multiple types of business data. Incumbents whose focus is primarily on analysis and modeling of financial, marketing or pricing data should be matched to Finance, Market Research or Pricing as appropriate.

May be internal operations-focused or external client-focused, working in conjunction with Professional Services and outsourcing functions.

We are looking for an experienced Data Scientist who has previously supported Healthcare software applications. The data scientist role involves solving technical, data-driven Healthcare problems using computer science, mathematical, predictive modeling, and statistical methods, & knowledge. This person will interact with teams from Account Management to Application Engineering and R&D, to conduct detailed analysis and experimentation to maximize the utility of predictive modeling, analytic and machine learning across Waystar's product line.

The role will focus on extending machine learning, predictive modeling, and analytic components to provide up-to-date intelligence to Healthcare providers maximizing outcomes.

An ideal candidate for this position can approach problem-solving challenges independently, has a strong attention to detail, and enjoys working in a fast-paced, collaborative, and team-based environment.

• Complete familiarity with various statistical and machine-learning techniques including classification, regression, dimension reduction, clustering, and various multivariate methods.
• Complete familiarity with empirical approaches to estimate performance of machine learning models including hold-out sets, cross-validation, leave-one-out testing.
• Understanding of orders of algorithms and how they scale.
• Demonstrated competency in R/Python predictive modeling.
• Demonstrated competency in RDBMS (e.g., SQL Server).
• Ability to code in 1+ general purpose programming language (C#, Java, etc.).
• Must be a quick-learner with the ability to multi-task in a fast-paced environment.
• Outstanding presentation abilities and the ability to communicate with all levels of the Business.
• Comfortable working in newly-forming, ambiguous areas where learning and adaptability are key skills.
• Outstanding communication and interpersonal skills.
• Must possess strong analytical, problem-solving, and writing skills.
• Proficient in Microsoft Office applications.
• Detail-oriented.
• Master of Science degree or higher in Computer Science, Statistics, or Mathematics is preferred.
• Aptitude for medical informatics is preferred.

• Works closely with Application Engineering, Product Management, and Operational teams in designing, experimenting‑with, and…