Machine Learning Scientist , NY

Office:
New York, NY
Department:
Data Science

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination.

And it’s why our business strategy centers on making journalism so good that it’s worth paying for.

The New York Times is a technology company committed to producing the world's most reliable and highest quality journalism. Our ability to do so relies on a talented team of expert technologists who help NYT learn from a tremendous abundance of data unique to this company.

The Algorithmic Recommendations and Audience Data Science team aims to help users discover content across the Times' website, apps and emails by applying algorithms that make use of information about our readers' behavior and our editorial judgment. We also build internal tools for the newsroom to better understand story performance and coverage trends. We are a group of machine learning scientists and data analysts that partner with teams across The New York Times.

We are looking for a Machine Learning Scientist to join the team and apply machine learning methods to meet this challenge. You will report to a Lead Machine Learning Scientist, and collaborate with partners across the company.

• You will reframe business and newsroom goals as machine learning tasks that deliver accurate predictions, relevant insights, and optimization
• You will adapt or develop machine learning algorithms in cases when existing algorithms are insufficient, while implementing simple approaches when appropriate
• You will implement and deploy machine learning research with robustness and reproducibility, with consideration of risks and trade-offs
• You will turn models into data products, collaborate with engineering teams, and integrate into processes throughout The Times
• You will communicate complex ideas in machine learning while collaborating with technical and non-technical colleagues in engineering, analytics, product management, marketing, editorial, and executive leadership groups
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

• PhD, MS + 2 years experience, or 3+ years work experience in machine learning, statistics, computational social science, applied mathematics, or another quantitative/computational discipline
• 2+ years experience with open source machine learning or statistical analysis tools
• 2+ years coding experience in Python
• 2+ years experience in SQL and manipulating large structured or unstructured datasets for analysis

• 1+ year of experience with recommendation systems, including content-based methods using natural language processing
• 1+ years of experience with deep learning architectures, including embedding methods and Pytorch or Tensorflow
• 1+ years of experience translating ambiguous business questions into machine learning problems
• 1+ years of experience building data products, either internal or consumer-facing

The annual base pay range for this role is between:

$121,000 — $131,000 USD

The New York Times Company is committed to being the world’s best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.

We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other…