Develop, validate, and deploy statistical and machine learning models that help identify member behaviors, such as engagement patterns, product adoption opportunities, and potential member dormancy or attrition.
Lead methodology design for controlled experiments to evaluate onboarding strategies, engagement programs, and marketing initiatives while ensuring statistical rigor and actionable insights.
Translate complex analytical findings into clear, compelling narratives using visualizations, dashboards, and presentations that support strategic decision-making.
Partner with marketing, product, analytics, and engineering teams to define business problems, gather requirements, and deliver data-driven solutions that improve member experiences.
Build and maintain intermediate to complex datasets—including structured and unstructured data—using tools such as Python, SQL, or Spark to support modeling and analysis.
Use analytical research and exploratory techniques to uncover trends, opportunities, and emerging insights that support divisional and organizational goals.
Participate in peer reviews, knowledge-sharing forums, and data science communities to promote high-quality analytics practices and continuous learning.
Monitor model performance, evaluate results, and optimize models over time to ensure continued accuracy, reliability, and business value.
Take on additional responsibilities and initiatives that support evolving data science priorities across the organization.

Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field, or equivalent combination of education and experience.
Minimum 2 years of experience in data science, including at least 1 year applying data science in a business or industry setting with proficiency in programming languages such as Python or R, with the ability to build, test, and deploy analytical models.
Working knowledge of statistical analysis and machine learning techniques, with the ability to apply them to real-world business problems.
Proven communication, presentation, and project management skills, with the ability to translate complex analytical findings into clear insights for diverse stakeholders.

Data Scientist

Key skills