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Data Scientist

3 months ago

Newark, United States Avispa Full time

Data Scientist - Product and Insights 1282622

A leading podcast and audiobook company is seeking a Data Scientist - Product and Insights. The successful candidate will operationalize existing Multimedia Mix Model (MMM) framework to cover all current company's marketplaces. The ideal candidate is a motivated, results-oriented Data Scientist with strong rigor and demonstrable skills in ML, DL, NLP, data mining and/or large-scale distributed computation. The company offers a great work environment

Data Scientist - Product And Insights Pay And Benefits

Hourly pay: $85-$95/hr Worksite: Leading podcast and audiobook company (Newark, NJ 07102 - Hybrid) W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL 40 hours/week, 6 Month Assignment

Data Scientist - Product And Insights Responsibilities

Operationalize existing Multimedia Mix Model (MMM) framework to cover all current company's marketplaces. Automate the data ingestion and orchestration of the model framework to ensure timely delivery of measurement. Deliver data science artifacts to improve the performance of the model. Develop and validate models to optimize the Who, When, Where and How of all our interactions with customers. Develop Amazon-scale data engineering pipelines. Imagine and invent before the business asks, and create groundbreaking applications using cutting-edge approaches. Develop compelling data visualizations. Work closely with other data scientists, ML experts, engineers as well as business across globe, and on cross-disciplinary efforts with other scientists. Contribute to the growth of the Audible Data Science team by sharing your ideas, intellectual property and learning from others.

Data Scientist - Product And Insights Qualifications

3-4 years of experience as a Sr. Data Scientist MS in one of the following disciplines: Computer Science, Statistics, Data Science, Economics, Applied Math, Operational Research or a related quantitative field plus 3+ yrs relevant experience; or, PhD plus 1+ yr relevant experience. Experience with graph neural networks, reinforcement learning. Experience with MCMC. Modeling, research design experience and exposure to cutting-edge algorithms. Experience with methods for causal inference using longitudinal data and more generally (panel, regression, diff-in-diff, etc.). Experience with Docker Container Platform. Experience with machine learning methods for Bayesian estimation and inference. Experience with Agile Software Development. Experience with R, RShiny, and Scala preferred. Fluent in SQL, Python. Exposure to software engineering environments (version control, command line…) Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions). Domain knowledge of comparable products (digital, retail) preferred. Big Data Engineering with Spark / AWS EMR & Glue preferred. Candidate must have the breadth and depth in various domains like Marketing Measurement, Causal Inference.

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