Senior Data Scientist
1 week ago
Senior Data Scientist, Product and Insights
About this role
The objectives of this fixed term contract are to 1) operationalize existing Multimedia Mix Model (MMM) framework to cover all current marketplaces 2) automate the data ingestion and orchestration of the model framework to ensure timely delivery of measurement and 3) deliver data science artifacts to improve the performance of the model.
About the team
The data science team partners with marketing, content, product, and technology partners to solve business and technology problems using scientific approaches to build product and services that surprise and delight our customers. We employ scalable cutting-edge machine learning (Client), deep learning (DL), and Natural Language Processing (NLP) knowledge to better target customers and prospects, understand and personalize the content, and context needed to optimize their book-listening experience. We operate in an agile environment in which we own and collaborate on the life cycle of research, design, and model development of relevant projects.
About you
We are looking for a motivated, results-oriented Data Scientist with strong rigor and demonstrable skills in Client, DL, NLP, data mining and/or large-scale distributed computation.
As a Senior Data Scientist, you will:
Develop and validate models to optimize the Who, When, Where and How of all our interactions with customers.
Develop TB-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, Client experts, engineers as well as business across globe, and on cross-disciplinary efforts with other scientists.
Contribute to the growth of the Data Science team by sharing your ideas, intellectual property and learning from others.
Basic Qualifications
Modeling, research design experience and exposure to cutting-edge algorithms.
MS in one of the following disciplines: Computer Science, Statistics, Data Science, Economics, Applied Math, Operational Research or a related quantitative field + 3 yrs relevant experience; or, PhD +1 yr relevant experience.
Experience with methods for causal inference using longitudinal data and more generally (panel, regression, diff-in-diff, etc.).
Fluency in English, both written and spoken.
Fluent in SQL, Python.
Exposure to software engineering environments (version control, command line...)
Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions).
Experience with Docker Container Platform.
Experience with machine learning methods for Bayesian estimation and inference.
Experience with Agile Software Development.
Preferred Qualifications
Domain knowledge of comparable products (digital, retail).
Big Data Engineering with Spark / AWS EMR & Glue.
Experience with R, RShiny, and Scala.
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