Senior Data Scientist

  • Lancaster, NY


: $107,173.33 - $200,310.00 /year *

Employment Type

: Full-Time


: Information Technology

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CitizenNet, a social data and marketing platform, which utilizes machine learning and artificial intelligence to put the right content, offer or advertisement in front of the right person at the right time is based in Los Angeles, CA and is led by CEO Dan Benyamin. The CitizenNet team is based in Los Angeles. Conde Nast's acquisition in February 2017 of CitizenNet deepens Conde Nast's data science talent and expertise and will be incorporated into Conde Nast's proprietary data product \"Conde Nast Spire,\" to expand the audience targeting and data capabilities of Conde Nast beyond the company's owned and operated properties to social platforms.. Job Description. Conde 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.. Conde 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 Conde Nast. Our mission is not only to inform readers but to ignite and nourish their passions.. We are seeking a Senior Data Scientist who will support a range of initiatives across various technological and business areas within Conde Nast.. Lead development of models that enable learning of semantics of data (our content that includes text, images and video). Devise better data driven models of user behavior. Work towards long-term ambitious research goals, while identifying intermediate milestones. 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 engineering teams to operationalize and integrate models into production environments.. MINIMUM QUALIFICATIONS. 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 machine learning, natural language processing, deep learning and other techniques appropriate for large-scale data modeling and analysis.. Experience manipulating and analyzing data from different sources.. Four or more years of relevant 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.. C onde Nas t 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 analyst, data analytic, data architect, data integration, data integrity, data management, data warehouse, data warehousing, database administrator, mongo database

* 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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