Careers at Dynamic Yield

Data Scientist

About Dynamic Yield

Dynamic Yield helps retailers, marketers and publishers maximize revenue by quantifying, optimizing and personalizing every customer interaction in real-time, across any channel. We are the world’s first personalization technology stack that offers personalization, recommendations, 1:1 messaging, testing and optimization - in a single platform.

Dynamic Yield personalizes the experiences of more than 500 million users globally each month and counts industry leaders like Sephora, PacSun, Rolling Stone, Europe’s fashion leader Lamoda, MakerBot and Liverpool Football Club among its many customers. Based in New York, the company has more than 100 employees in five offices worldwide.

We like self-starters, we have a clear company mission, and we value those who step up with fresh ideas on how to achieve it.

Our growing Data Science team is in charge of prototyping and evaluating algorithms that make key decisions in our product platform. While we handle all aspects of machine learning, statistics and other in-house algorithms at Dynamic Yield, we are focused on a couple of fields: recommendation systems, reinforcement learning and predictive analytics. We take machine learning ideas all the way from early research to deployment in production, and implement a wide spectrum of approaches and algorithms for a wide range of use cases. In addition, as the local mathematical/statistical authority, we take part in a wide variety of decisions regarding different aspects of the product, from data collection to UI reports and more. We work closely with a dedicated development team that takes our prototypes to production, and make data more accessible for our research. We employ cutting edge Big Data technologies such as Apache Spark.

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  • Strong Data Science background (Bsc. or above in CS/Math/Statistics etc..).
  • Practical machine learning experience.
  • 1-2 years of relevant experience.
  • Hands on coding experience (Python, Java/Scala).
  • Data exploration skills.
  • Strong communication skills.
  • Creative, result-driven, self starter, quick learner and a team player.


  • Formal background in statistics.
  • Research experience in a quantitative field.
  • Experience with online learning, reinforcement learning, or recommendation systems.
  • Thorough understanding of map-reduce paradigm, and Hadoop/Spark experience.
  • Strong Scala/Java coding abilities.


New York

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