Data Scientist II

About the 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.

About the Role : 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, segmentation, and user behaviours.

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

Qualifications : Applicants should have a degree (B.S. or higher) in a technical discipline or relevant professional experience.

Required Skills :

4-7 years of machine learning experience in industry or academia

Experience in one or more areas of advanced data science (NLP, Deep Learning, Computer Vision, etc.)

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