Data Scientist

Compensation

: $115,435.00 - $200,310.00 /year *

Employment Type

: Full-Time

Industry

: Information Technology



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Cond Nast is a premier media company renowned for producing the highest quality content for the world's most influential audiences. Attracting more than 100 million consumers across its industry-leading print, digital and video brands, the company's portfolio includes some of the most iconic titles in media: Vogue, Vanity Fair, Glamour, Brides, Self, GQ, GQ Style, The New Yorker, Cond Nast Traveler, Allure, Architectural Digest, Bon Apptit, Epicurious, Wired, W, Golf Digest, Golf World, Teen Vogue, Ars Technica, The Scene, Pitchfork and Backchannel. The company's newest division, Cond Nast Entertainment, was launched in 2011 to develop film, television and premium digital video programming. For more information, please visit condenast.com and follow @CondeNast and @CondeNastCareer for Twitter and @condenastcareers for InstagramJob DescriptionCond Nast is a premier media company renowned for producing the highest quality content for the world's most influential audiences, attracting more than 100 million consumers across its industry-leading print, digital and video brands.Cond Nast is home to many of the world's most-celebrated magazine and website brands. The company's reputation for excellence is the result of our commitment to publishing the best consumer, trade, and lifestyle content. Our brands include Vogue, Epicurious, Vanity Fair, The New Yorker, Wired, and many more. Passion is the core of our philosophy at Cond Nast. Our mission is not only to inform readers but to ignite and nourish their passions.We are seeking Data Scientists who will support a range of initiatives across various technological and business areas within Cond Nast.RESPONSIBILITIES* Conduct statistical analysis of content as well as consumer web, demographic, behavioral, and transactional datasets in support of strategic initiatives.* Design tests, benchmarks, and track the performance of analytic solutions over time.* Work with both management and organizational peers to improve results by applying quantitative analysis, data mining, and machine learning methods to ongoing activities.* Design and present recommendations to guide future business and research directions.* Work with partners in Data Engineering, Marketing, Product, Sales, and Ad Operations teams to operationalize and integrate models into production environments.MINIMUM QUALIFICATIONS* BS, MS, Ph.D., or equivalent industry experience in Computer Science, Mathematics, or other related STEM (science, technology, engineering, and math) fields.* Exceptional quantitative and statistical skills, including experience with regression, clustering, machine learning, natural language processing, deep learning and other techniques appropriate for large-scale data modeling and analysis.* Two or more years of business/marketing analytics experience, preferably in a consumer-based organization.* Exceptional communication skills, particularly in communicating and visualizing quantitative findings in a compelling and actionable manner for business stakeholders.* Proficiency in Python, SQL, Julia, or R.* Experience with Hadoop, Pig, Hive AWS EMR, Spark, Flink, or Beam.What happens next?If you are interested in this opportunity, please apply below and we will review your application as soon as possible. Please note that due to the high level of applications we receive, it is not always possible for us to respond to each applicant in person. Should your profile fit this open position we will contact you within approximately 4 weeks. You can update your resume or upload a cover letter at any time by accessing your candidate profile.Cond Nast is an equal opportunity workplace.Duties and responsibilities may be adjusted based on years of experience.Salary is also commensurate with experience.
Associated topics: data administrator, data analyst, data architect, data integrity, data manager, data scientist, data warehouse, database, mongo database administrator, sybase * The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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