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Data Scientist II

4 weeks ago

Udaipur, Rajasthan, India Condé Nast Technology Lab Full time

About Company: Condé Nast is a premier media company renowned for producing the highest quality content for the world's most influential audiences, attracting over 100 million consumers across its industry-leading print, digital, and video brands.

Condé 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 Condé Nast. Our mission is not only to inform readers but to ignite and nourish their passions.

As a member of the Data Science and Machine Learning Engineering (DS/MLE) team you will be the technical expert for a team that builds models for initiatives such as image recognition, recommender systems, NLP, LLMs, segmentation, and user behaviors.

About Responsibilities:

Responsibilities include, but are not limited to:

  • Participate in model design, testing, and execution
  • Work closely with data engineers and machine learning engineers to deliver products and analyses
  • Develop advanced machine learning algorithms and proof of concepts
  • Experiment and Innovate in applications of machine learning to Conde Nast's Business problems
  • Provide technical expertise to junior team members

MINIMUM QUALIFICATIONS

  • Applicants should have a degree (B.S. or higher) in technical discipline or relevant professional experience
  • Bachelor's with 4-8 years of machine learning experience in industry/academia
  • Experience in one or more areas of advanced data science (NLP, Deep Learning, Computer Vision, etc.) NLP/LLMs experience strongly preferred
  • Experience in statistical analysis and experiment design
  • Software development skills with proficiency in Python
  • Experience with machine learning frameworks such as TensorFlow, JAX, PyTorch, Spark MLlib, Keras, or scikit-learn
  • Strong communication skills including to non-technical audiences
  • Proven attention to detail, critical thinking, and the ability to work both independently and collaboratively within a cross-functional team