| Data Scientist-Remote at Remote, Remote, USA |
| Email: [email protected] |
| From: sravani, Nitya INC [email protected] Reply to: [email protected] Role Data Scientist Remote Yes Location - US West coast time preferred (or can support west coast time) Level: L5 (senior L5 resource) Duration: 6 months (can be extended based on performance) Expected start date: 8/5 or sooner if available Interview process: 2 stage as before An ideal candidate (Data Scientist) will have extensive experience in causal inference and ML prediction, and proven experience in leveraging causal and/or ML 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/ML Skills * Causal Inference Modeling (e.g., experimentation and/or observational model) * ML 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 ML 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 Keywords: machine learning sthree active directory rlang Data Scientist-Remote [email protected] |
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| Wed Jul 31 01:07:00 UTC 2024 |