At Noom, we use scientifically proven methods to help our users create healthier lifestyles, and manage important conditions like Type-II Diabetes, Obesity, and Hypertension. Backed by top VC's, Noom has grown revenue 20X in just 2 years. To continue growing, we are seeking an exceptionally talented Data Scientist to work with our Growth Acquisition team.
We are looking for an experienced Data Scientist with an interest in marketing data science. You will be working closely with our Growth Acquisition team at the forefront of Computational Marketing, trying to solve the puzzle of building a brand while maximizing marketing efficiency. Through your insights and advancements, you will improve the efficiency of our $200M+ annual ad spend.
What you’ll like about us
- We work on problems that affect the lives of real people. Our users depend on us to make positive changes to their health and their lives.
- We base our work on scientifically-proven, peer-reviewed methodologies that are designed by medical professionals.
- 9-figure annual marketing budget and data-driven company through and through.
- We’re a respectful, diverse, and dynamic environment in which Engineering is a first-class citizen, and where you’ll be able to work on a variety of interesting problems that affect the lives of real people.
- We offer a generous budget for personal development expenses like training courses, conferences, and books.
- You’ll get three weeks’ paid vacation and a flexible work policy that is remote- and family-friendly (about 50% of our engineering team is fully remote). We worry about results, not time spent in seats.
What we’ll like about you
- You have 4+ years of experience as a Data Scientist or Data Analyst in a similarly-sized organization, with a proven record of analysis and research that positively impacts your team.
- You possess a deep understanding of Marketing Data Science, with excellent communication skills and the ability to clearly communicate technical concepts to a non-technical audience.
- You possess excellent SQL/relational algebra skills, ideally with at least a basic knowledge of how different types of databases (e.g.: column vs row storage) work.
- You have a superior knowledge of statistical analysis methods, such as input selection, logistic and standard regression, etc.
- You are comfortable writing Python code, and have good working knowledge of pandas and numpy. We don’t expect you to write production-quality code, but you should have some programming experience.
- You are comfortable with at least “medium data” technologies and how to transcend the “memory bound” nature of most analytics tools.