* We are developing a cutting-edge promotion operating system that helps brands manage, analyze and optimize their promotional spend. Our system uses Causal Machine Learning to analyze the incrementality of promotions and help our customers optimally invest their promotion budgets.
* We believe causality is the best way for companies to act on their data. If you do too, you might be a good fit!
Responsibilities
* Analyze raw event data, decide which data is desirable, and structure the data in a useable way
* Create data transformations that are easy to consume in real time
* Build real time and batch prediction models using Causal ML for users incremental lift
* Design complex experiments that TEST reactions to different treatments
* Collaborate with engineering team to bring Machine Learning models to production
* Generate actionable insights for our customers
* Suggest potential areas of explorations based on business impact
* We believe causality is the best way for companies to act on their data. If you do too, you might be a good fit!
Responsibilities
* Analyze raw event data, decide which data is desirable, and structure the data in a useable way
* Create data transformations that are easy to consume in real time
* Build real time and batch prediction models using Causal ML for users incremental lift
* Design complex experiments that TEST reactions to different treatments
* Collaborate with engineering team to bring Machine Learning models to production
* Generate actionable insights for our customers
* Suggest potential areas of explorations based on business impact
Requirements:
* Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
* At least 4 years of experience in a data Science role
* Full ( data Science) Stack experience: data pipelining, model building, experimentation, and analysis/reporting
* Strong working knowledge of SQL: ability to dive into raw data and debug problems
* Deep understanding of Machine Learning algorithms and experience with production pipelines. Advantage: experience with Causal Inference, multi-armed bandits
* Experience setting up data /ML pipelines in production environments (e.g. working with MLOps, DBT, etc.)
* Experience with designing A/B tests in complex environments
* Fluency in Python
* Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
* At least 4 years of experience in a data Science role
* Full ( data Science) Stack experience: data pipelining, model building, experimentation, and analysis/reporting
* Strong working knowledge of SQL: ability to dive into raw data and debug problems
* Deep understanding of Machine Learning algorithms and experience with production pipelines. Advantage: experience with Causal Inference, multi-armed bandits
* Experience setting up data /ML pipelines in production environments (e.g. working with MLOps, DBT, etc.)
* Experience with designing A/B tests in complex environments
* Fluency in Python
This position is open to all candidates.
