Sr. Data Scientist

GoTo Meeting

Lehi (UT)

On-site

USD 80,000 - 120,000

Full time

14 days+

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Benefits offered by this job

Competitive total rewards
Customizable benefits package
Generous paid time off
Paid parental leave
Education assistance
401(k) program with company match
Pet insurance

Job summary

GoTo Meeting is seeking an experienced Data Scientist to enhance healthcare software by applying statistical methods, machine learning, and predictive modeling. This role involves collaborating with various teams to solve healthcare-related data challenges, ensuring the delivery of impactful analytics and results.

The ideal candidate should possess strong analytical abilities, experience in R/Python, and excellent communication skills. A master’s degree in a relevant field is preferred. The position offers a supportive work environment and various benefits.

Qualifications

  • Complete familiarity with statistical and machine learning techniques.
  • Understanding of algorithmic complexity and model performance estimation.
  • Quick learner with multitasking capabilities in a fast-paced environment.

Responsibilities

  • Design and implement machine learning systems for healthcare applications.
  • Collaborate with teams to analyze data and surface features.
  • Translate healthcare problems into mathematical frameworks.

Skills

Statistical techniques
Machine learning
Predictive modeling
R/Python
SQL Server
C#/Java
Analytical skills
Communication skills

Education

Master's degree in Computer Science, Statistics, or Mathematics

Tools

Microsoft Office

Job description

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, mathematics, predictive modeling, statistical methods, and 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, analytics, 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 and maximize outcomes. An ideal candidate can approach problem‑solving challenges independently, has a strong attention to detail, and enjoys working in a fast‑paced, collaborative, team‑based environment.

WHAT YOU'LL DO
  • Work 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.
  • Work closely with Application Engineering teams to gather and process data and to surface analytically based features in core products.
  • Work on groundbreaking new applications of machine learning and analytic technology to healthcare, producing quantitative, justifiable results to guide feature planning.
  • Translate real‑world healthcare problems to mathematical frameworks.
  • Work with Product Management, Marketing, and Sales as needed to promote sales and 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.
  • Understand, organise, and communicate root causes of problems and successes succinctly.
WHAT YOU'LL NEED
  • Complete familiarity with 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, and leave‑one‑out testing.
  • Understanding of algorithmic complexity and how they scale.
  • Demonstrated competency in R/Python predictive modeling.
  • Demonstrated competency in RDBMS (e.g., SQL Server).
  • Ability to code in one or more general‑purpose programming languages (C#, Java, etc.).
  • Quick learner with the ability to multitask in a fast‑paced environment.
  • Outstanding presentation abilities and strong communication with all levels of the business.
  • Comfortable working in newly‑formed, ambiguous areas where learning and adaptability are key skills.
  • Outstanding communication and interpersonal skills.
  • Strong analytical, problem‑solving, and writing skills.
  • Proficiency 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.
WAYSTAR PERKS
  • Competitive total rewards (base salary + bonus, if applicable).
  • Customizable benefits package (3 medical plans with Health Saving Account company match).
  • Generous paid time off for non‑exempt team members – starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. Flexible time off for 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.

Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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