Senior Data Scientist

Our mission is to unlock the full potential of ZI’s extensive B2B data by applying machine learning (ML) and Generative AI to optimize the full Go-to-Market stack. We’ve cultivated a powerful blend of product thinking, modern AI expertise, and iterative methodologies which have delivered a robust suite of data products that inject data-driven intelligence into every facet of ZI. We actively explore existing solutions, adapting them to suit our unique needs while fostering a culture of creativity. Collaboration is at our core, as we work closely with data scientists, product managers, ML engineers, subject-matter experts, and key stakeholders to identify critical gaps and effective solutions to the most valuable problems in our business. The result? An impressive array of both experimental and production-ready AI products that have a tangible impact on our customer’s ability to generate revenue with their Go-to-Market motion. Embrace the opportunity to join our accomplished team on this transformative journey, where innovation and teamwork thrive, and where your contributions will shape the future of data-driven Go-to-Market.

What you will do:

As part of our Innovation Data-Science team, you will be working on building out our recommendation and ranking systems stack which will support a variety of business use cases:

• Tell our customers who they should reach out to next, what action they should take, and why. 
• Identify key signals that drive a user's next best action in order to optimize sales outcomes using advanced probability, statistics, predictive performance, and ML/RL.
• Design and implement state-of-the-art recommender systems to identify high-intent companies and contacts, optimizing customer engagement and conversion rates over time.
• Build innovative new AI solutions, enhance existing models, drive continuous improvement and keep us ahead of industry trends. Promote a culture of continuous learning and knowledge sharing within the team.

• Partner with ML engineers to review and co-optimize technical designs. Support the productionization and deployment of data science models and pipelines, ensuring scalability, reliability, and efficiency in real-world applications.

What you will bring:

• Experience: MS + 5yrs or PhD + 3yrs in quantitative field: Statistics, Applied Math, Computer Science, Physics or equivalent. 
• 2+ yrs building personalized recommender systems, employing advanced techniques such as deep learning-based models, sequential recommendation algorithms, reinforcement learning frameworks, and/or dynamic re-ranking. 
• Skilled in continuous model evaluation and adaptation to evolving user preferences and behavior patterns based on real-world feedback.
• Data-Centric Mindset: Be willing to explore the data and have it guide you to the best solution. Able to utilize a diverse range of advanced statistical and analytic techniques to inform development priorities and decision-making processes.
• Languages and Compute Frameworks: Able to write readable, testable, maintainable and extensible code in Python, SQL, and Spark. Bonus points for Ray.
• Production ML: Experience developing data preparation, model training and inference pipelines using cloud-managed tools like Dataproc, EMR, Airflow, vector databases (FAISS, Pinecone), or equivalent. 
• ML Frameworks: Deep experience w/ PyTorch, XGBoost, SparkML, model registries (Hugging Face), LLM APIs, etc. 
• Theory: Understanding of latest deep learning architectures and when to apply a given pre-trained model. Some experience with techniques like prompt engineering, fine tuning, reinforcement learning w/ human feedback, model distillation and model compression. Up-to-date on recent advances in the LLM space.
• Communication: Able to navigate large projects with multiple collaborators. Excellent cross-functional and verbal communication skills, enabling seamless communication with business partners and stakeholders.

 

The US base salary range for this position is  $161,600.00 -  $202,000.00  + bonus , equity and benefits.

Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and/or training. Your recruiter can share more information about the specific salary range for your desired work location during the hiring process.

We want our employees and their families to thrive. In addition to comprehensive benefits we offer holistic mind, body and lifestyle programs designed for overall well-being. Learn more about ZoomInfo benefits here.