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Job Details

Requisition Number 16-0608
Post Date 6/28/2017
Title Senior Data Scientist
Organization Name Pronoun
City New York
State NY
Description
Pronoun is a digital book publishing platform owned by Macmillan Publishers. Pronoun’s mission is to build a new model for independent publishing that puts authors first while bringing smarter technology and data to traditional prestige publishing.

Macmillan is a group of media companies in the United States held by Verlagsgruppe Georg von Holtzbrinck, based in Stuttgart, Germany, which publishes a wide range of books, magazines, and digital products for the consumer and education markets. Our American publishers include Farrar, Straus and Giroux, Henry Holt & Company, W.H. Freeman and Worth Publishers, Bedford/St. Martin’s, Picador, Roaring Brook Press, St. Martin’s Press, Tor Books, Hayden McNeil, Macmillan Children’s Group, Macmillan Audio and Bedford Freeman & Worth Publishing Group.

We are an Equal Opportunity Employer committed to reflecting a broad representation of differences — race, ethnicity, religion, sex, sexual orientation, gender identity/expression, physical ability, age, family status, economic background and status, geographical background and status, and perspective — in our workplace.
Requirements
Our mission is to build a new model for book publishing that puts authors first. We’re creating the tools, technology, and information that authors and publishers need to con continually help more readers discover and purchase their books online. As part of Macmillan, we’re bringing advanced decision support to traditional book publishing. We operate as a startup with the resources and access of a larger company.

Massive Data

One of our biggest technical differentiation's is a unique data set at massive scales. Over the past five years we have been collecting millions of structured and unstructured data points each day for 7 million books and growing. We are now looking for an experienced leader to help us mine and transform this data into a competitive advantage for our authors. Hands-on experience in wrangling data at this scale across a variety of AWS stores is a must.

You

You are a seasoned data scientist with product experience and a broad toolset in data mining, statistical machine learning, and optionally natural language processing. You are a strong problem solver; you work effectively with others to understand a problem and are also self-motivated to research techniques and technologies as needed. You will work closely with product management and engineering to lead the definition, testing, and validation of hypotheses given a business objective. You will also be responsible for communicating the results and assisting in integrating the developed solution into the product. To achieve this you must demonstrate theoretical and practical understanding of various algorithms and techniques including:

1. Feature generation and selection techniques
2. Machine Learning algorithms (supervised, unsupervised, semi-supervised, probabilistic models)
3. Fundamentals of linear and nonlinear optimization and regularization techniques
4. Model selection and validation techniques (cross and k-fold validation, Bayesian optimization)
5. High dimensional data visualization techniques and platforms
6. Data extraction and normalization from disparate sources: (No) SQL DBs and APIs
7. Software engineering practices and design principles
8. Experimental methods, including AB testing

Above all, you should be able to communicate complicated technical concepts effectively and clearly to managers and engineers, to incorporate feedback and guidance into your priorities and direction, and to help the organization make smart decisions about selecting realistic and valuable business objectives.

Technical Skills & Background

1. Machine learning platforms/frameworks (SciPy, SciKit, MLib, Torch, Tensorflow)
2. Big data tools (Hadoop/Spark)
3. Visualization (D3, ggplot2, Tableau)
4. Programming languages (e.g., Python, Java, Lua, R)
5. SQL, and the AWS ecosystem
6. A working understanding of linux (bash commands and scripting)
7. A plus: Natural language processing (word2vec, Stanford NLP, OpenNLP, Gate, Spacy)

Educational Background

● Bachelor’s degree in a quantitative field (e.g., economics, econometrics, statistics, finance, the sciences) required. Advanced degree a plus.
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