Sr. Data Scientist

Waystar • Lehi, UT

4d

About The Position

ABOUT THIS POSITION 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.

Requirements

• 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 the fields of Computer Science, Statistics, or Mathematics is preferred

Nice To Haves

• An aptitude for medical informatics is preferred

Responsibilities

• Works closely with Application Engineering, Product Management, and Operational teams in designing, experimenting-with, and implementing machine learning and analytical systems applied to design information and user behavior
• Works closely with Application Engineering teams to gather and process data, as well as in surfacing various analytically-based features in core products
• Works on groundbreaking new applications of machine learning and analytic technology to Healthcare, producing quantitative, justifiable results to guide feature planning
• Translates real-world Healthcare problems to mathematical frameworks
• Works with Product Management, Marketing, and Sales as needed to promote sales and to incorporate market and customer feedback
• Data exploration, hypothesis creation (from business and product goals), testing algorithms, scaling to large data-sets and validating results will be common tasks for this role
• Understands, organizes, and communicates root causes of problems and successes succinctly

Benefits

• Competitive total rewards (base salary + bonus, if applicable)
• Customizable benefits package (3 medical plans with Health Saving Account company match)
• We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
• Paid parental leave (including maternity + paternity leave)
• Education assistance opportunities and free LinkedIn Learning access
• Free mental health and family planning programs, including adoption assistance and fertility support
• 401(K) program with company match
• Pet insurance
• Employee resource groups

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level