Staff Data Scientist, Marketing Inference
Company: RemoteHunter
Location: Location not specified (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-07-07
About this role
1. About Our Client:
The organization operates in the mental health care industry, addressing the challenge of limited accessibility to therapy services. Founded in 2013, it has grown to become the world''s largest online therapy service, connecting millions of people with affordable and convenient therapy through a network of over 30,000 licensed therapists. The company is committed to expanding access to mental health care as the demand for these services continues to rise.
2. About the Opportunity:
The Staff Data Scientist, Marketing Inference role focuses on scaling and optimizing marketing efforts through advanced data analysis. This position involves developing and maintaining marketing models to improve efficiency and support decision-making. The role contributes to the organization by providing data-driven insights that enhance marketing strategies and increase the impact of mental health services.
3. Responsibilities:
• Analyze large and complex data sets to generate actionable insights.
• Partner with the marketing team to identify and test data-driven ideas for improving marketing efficiency.
• Develop, implement, and maintain marketing models, including Bayesian Marketing Mix Models and Multi-Touch Attribution models.
• Monitor and analyze marketing uplift tests using rigorous statistical methods.
• Present data and insights to stakeholders to guide marketing decisions.
• Design testable models and algorithms addressing complex problems with measurable business impact.
4. Requirements:
• Bachelor’s or Master’s degree in Statistics, Mathematics, Economics, Computer Science, Operations Research, Engineering, or a related quantitative field.
• 5 to 8 years of experience in quantitative data analysis involving user behavior and large data sets.
• Strong expertise in statistics, hypothesis testing, and experimental design.
• Experience analyzing A/B tests and advanced statistical methods such as difference-in-difference and regression discontin...