You will partner closely with Game Directors, Product Managers, and our central analytics teams to drive value across Zynga's diverse portfolio. If you are a leader who is "bilingual" in data-possessing deep Data Science expertise to guide methodology while bringing high MLE and Engineering skills to build scalable, production-ready systems-we want to hear from you.
Key Responsibilities
Team Leadership & Mentorship: Recruit, retain, and develop top-tier talent within the Data Science & MLE team. Foster an inclusive culture of innovation where technical rigor meets creative problem-solving.
Technical Direction & Engineering Standards: Act as the hands-on Technical Lead for the domain. You will supervise the end-to-end development lifecycle-from research to production-enforcing high standards and MLOps to ensure our models are scalable and maintainable.
Strategic DS & Analytics Support: Drive the development of advanced analytical frameworks to solve core business challenges. You will guide the team in applying rigorous statistical and machine learning methods to areas such as Time Series Forecasting, Causal Inference, Marketing Optimization, Root Cause Analysis, and more.
Strategy & Collaboration: Partner with Game Directors, BI Platform PMs, and embedded analytics teams to define the data strategy and roadmap. You will ensure that our technical initiatives are directly aligned with company-wide goals and solving the right problems.
Global Alignment: Maintain a tight collaborative network with Data Science & Analytics managers in North America, ensuring global consistency in methodologies, knowledge sharing, and joint development.
Required Qualifications
Experience: 5-10 years of experience in data science or machine learning roles, with 3+ years of experience in people management.
Technical Proficiency: Expert proficiency in SQL and Python. You must be capable of writing and reviewing production-grade code and have hands-on experience with cloud environments (GCP, AWS, Databricks).
Modeling Expertise: Strong background in Classical ML, Deep Learning, and familiarity with Generative AI (LLMs, Multimodal embeddings, Langchain or like technologies).
Engineering Mindset: Proven ability to bridge the gap between Research and Engineering. Experience deploying models to production and maintaining them is essential.
Education: Masters degree in Computer Science, Math, Statistics, or a related quantitative field; a PhD is strongly preferred.
Preferred Qualifications
Experience in the mobile gaming industry or high-velocity B2C tech environments.
Passion for gaming and experience playing various game genres.
Familiarity with modern data platforms (e.g., Vertex AI, Cloud Run, Sage).
