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ZoomInfo is seeking a Senior Data Scientist to join our Innovation Data Science team to develop Signal Relevancy models that power our industry-leading B2B sales and marketing intelligence platform. If you are a visionary data scientist with expertise in Recommender Systems, Scoring Models, Sentiment Modeling, NLP, and LLMs, this is an exciting opportunity to shape how businesses identify and act on the most valuable market signals.

About our Team

Our mission is to unlock the full potential of ZoomInfo’s extensive B2B data by applying ML and Generative AI to extract meaningful topics, trends, and entities that optimize the full Go-to-Market stack. We combine deep expertise in modern AI techniques, NLP, NER, and iterative methodologies to develop high-impact AI-powered data products. Our solutions help customers understand market trends, detect emerging topics, and identify key business signals. We collaborate closely with data scientists, product managers, ML engineers, and domain experts to build state-of-the-art NLP models that drive customer engagement and sales intelligence.

What you will do:

As part of our Innovation Data Science team, you will be working on developing and deploying NLP models that extract, classify, and structure unstructured text data to support key business use cases:

• Design and implement advanced scoring models to rank and prioritize business signals based on relevance, intent, and predictive value.
• Develop and optimize recommender systems that suggest the most impactful signals, actions, and contacts to our users.
• Apply Sentiment Modeling and NLP techniques to extract insights from unstructured text, including news, emails, transcripts, and customer interactions.
• Leverage Large Language Models (LLMs) like BERT, GPT, and transformer-based architectures to enhance entity recognition, relationship mapping, and trend detection.
• Build scalable ML pipelines to process and score signals in real time, ensuring high performance and accuracy in production.
• Collaborate with ML engineers to deploy models using cloud-based infrastructures (AWS, GCP, Azure) and distributed computing frameworks (Spark, Ray, etc.).
• Continuously evaluate and refine models based on user feedback, A/B testing, and real-world performance metrics.
• Stay ahead of the latest research in recommender systems, NLP, and AI-driven scoring models, ensuring our solutions remain cutting-edge and industry-leading.

What you will bring

• MS + 5 years or PhD + 3 years in a quantitative field (Computer Science, AI, ML, EE, Physics, Applied Math, etc.).
• Deep expertise in Recommender Systems, Scoring Models, and Signal Ranking Algorithms.
• Strong experience in Sentiment Analysis, NLP, and BERT-based transformer models.
• Proficiency in Python, SQL, and distributed computing frameworks (Spark, Ray, Dask).
• Hands-on experience with ML frameworks (PyTorch, TensorFlow, Hugging Face, Transformers).
• Familiarity with LLM APIs, fine-tuning techniques, model optimization (distillation, reinforcement learning with human feedback, model compression).
• Experience developing scalable ML pipelines using cloud tools like Dataproc, EMR, Airflow, FAISS, Pinecone, or equivalent.
• Strong ability to communicate complex ML concepts to cross-functional teams and business stakeholders.
• A data-driven mindset, capable of exploring vast datasets to extract meaningful insights and drive business impact.