Staff Data Scientist, Marketing Inference

BetterHelp

6h•$170,000 - $220,000•Remote

About The Position

BetterHelp is looking for a Staff Data Scientist to help us scale and increase our impact. You will use cutting-edge methods to optimize our marketing efforts. The ideal candidate would have experience analyzing large and complex data sets related to web products. You'll be contributing to efforts in marketing inference, including our Marketing Mix Model and Attribution.

Requirements

BSc/MA in a quantitative discipline such as Statistics, Math, Economics, Computer Science, Operations Research, or Engineering
At least 5-8 years of experience in a quantitative data analysis role involving user behavior (e.g. marketing, product, UI/UX) and large data sets
Expertise in statistics, especially as it relates to hypothesis testing and experiment design
Experience analyzing A/B tests as well as experiments with more advanced statistical methods like difference-in-difference, regression discontinuity, or other methods that deal with network effects or panel data
Experience building predictive models and causal inference models
Experience analyzing large and complex data sets to drive business insights and decisions
Expertise in using tools like R and Python for data analysis
Proven success supporting or making business decisions based on your data analysis
Excellent communication skills, with experience simplifying complex topics and communicating technical ideas with non-technical audiences.
Advanced experience with SQL

Nice To Haves

Experience with Bayesian modeling methods
Experience with Marketing Mix Models and Multi-Touch Attribution models
Experience analyzing two-sided marketplaces
Experience with B2C, marketplace products
Experience with BI tools like Tableau and Looker

Responsibilities

Get insight from an enormous amount of data, and take a proactive role partnering with the marketing team in finding and testing data-driven ideas for improving our efficiency.
Contribute to the development, implementation, and maintenance of our marketing models, including a Bayesian Marketing Mix Model and a Multi-Touch Attribution model.
Monitor and analyze marketing uplift tests with statistical rigor, present the data and insights to the team, and drive marketing decisions.
Look at complex problems and come up with testable models and algorithms that have measurable business impact.
Enjoy great teamwork, have lots of fun, and take pride in building a world-class product that makes a difference in people's lives.