Company:
Ampcus Incorporated
Location: Seattle
Closing Date: 07/11/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
Role – Data Scientist
Location - Remote
Type – Contract
Candidate Must have strong research background in causal inference modeling.
An ideal candidate (Data Scientist) will have extensive experience in causal inference and Client prediction, and proven experience in leveraging causal and/or Client modeling to generate valuable business insights preferably in the marketing or ad domain.
This candidate must be able to communicate in writing their findings and be comfortable present them to diverse stakeholders including other scientists and business leaders, be comfortable creating structure for ambiguous business problems, and be adept at providing scalable solutions.
Required Skills (Must Have):
Econometric/Client Skills
* Causal Inference Modeling (e.g., experimentation and/or observational model)
* Client prediction modeling (e.g., LLMs, Transformer Model)
* Bayesian Statistics
* Data Visualization
* Double Machine Learning
* Regression
* Classifications
Technical Skills
* Python (Numpy, pandas, scikit etc.)
* SQL
* R
* Spark
* AWS platforms such as S3, Glue, Athena and Sagemaker
Experience:
* Project experience in building and validating causal inference and Client prediction models
* Project experience in building LLM transformer model
Preferred Skills (Nice to have):
* Experience in managing projects with large data sets and working with cross-functional teams
* Experienced in analysis of large data sets within e-commerce and/or advertising industries
* Project experience model deployment
Education (Preferred/Nice to Have)
* PhD in Economics, Data Science, Machine Learning, Statistics, Computer Science or closely related field
Location - Remote
Type – Contract
Candidate Must have strong research background in causal inference modeling.
An ideal candidate (Data Scientist) will have extensive experience in causal inference and Client prediction, and proven experience in leveraging causal and/or Client modeling to generate valuable business insights preferably in the marketing or ad domain.
This candidate must be able to communicate in writing their findings and be comfortable present them to diverse stakeholders including other scientists and business leaders, be comfortable creating structure for ambiguous business problems, and be adept at providing scalable solutions.
Required Skills (Must Have):
Econometric/Client Skills
* Causal Inference Modeling (e.g., experimentation and/or observational model)
* Client prediction modeling (e.g., LLMs, Transformer Model)
* Bayesian Statistics
* Data Visualization
* Double Machine Learning
* Regression
* Classifications
Technical Skills
* Python (Numpy, pandas, scikit etc.)
* SQL
* R
* Spark
* AWS platforms such as S3, Glue, Athena and Sagemaker
Experience:
* Project experience in building and validating causal inference and Client prediction models
* Project experience in building LLM transformer model
Preferred Skills (Nice to have):
* Experience in managing projects with large data sets and working with cross-functional teams
* Experienced in analysis of large data sets within e-commerce and/or advertising industries
* Project experience model deployment
Education (Preferred/Nice to Have)
* PhD in Economics, Data Science, Machine Learning, Statistics, Computer Science or closely related field
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