We create a safe space for communities to thrive.
OpenWeb’s mission is to improve the quality of conversations online, building a healthier web where content creators of all kinds are empowered to thrive. As a product company, OpenWeb partners with publishers and brands to build strong, direct relationships with their audiences.
OpenWeb’s technology empowers its partners to build vibrant communities rooted in healthy conversations and robust social experiences. OpenWeb works with more than 1,000 top-tier publishers, hosting more than 100 million active users each month.
Founded in 2015, OpenWeb has nearly 300 employees in New York City, Tel Aviv, Kyiv, San Diego, Canada, London, and Paris and is backed by world-class investors, including Georgian, Insight Partners, Entrée Capital, The New York Times, Samsung Next, Dentsu, and ScaleUp. To date, the company has raised $393 million in funding and is currently valued at $1.5 billion.
What You'll Do:
Design and Implementation . Responsible for designing and implementing data science solutions and products that optimize business outcomes. Balancing Short and Long-Term Goals . Identify and decide on promising research and development directions, balancing short-term and long-term goals. Best Practices . Implement best practices, processes and infrastructure for deploying end-to-end machine learning solutions in production, catering to various use cases including predictions, audience analysis, recommendation engines, Anomaly detection and NLP. Domain knowledge : Experience creating solutions for either of the following is an advantage: web behavior analytics, advertising targeting, conversation technology, financial prediction models, recommendation/personalization engines) Collaborative Data-Driven Opportunity . Work closely with product and business counterparts to identify opportunities where data science should be leveraged to optimize significant outcomes. What You'll Bring:
5+ years of successful track record as a Data Scientist implementing data science solutions to achieve commercial goals. Deep Knowledge with NLP/LLMs Proficiency with Python/Scala Practical experience with big data processing engines (such as Spark or Hadoop) and ML frameworks (such as SageMaker, Databricks) Experience with structured and unstructured data engineering relevant features from them. Some knowledge about one of the following: Codebase management, ML experiment tracking, inference APIs Experience in MLOps - an advantage Bachelor’s/Master degree in Computer Science, Applied Mathematics, Engineering, or any other technology-related field/experience.