Senior  Lead  Data Scientist, Graph & Forecasting

Dynata is seeking a Senior   Lead  Data   Scientist for Graph & Forecasting to lead the development of predictive intelligence capabilities that power key operational, commercial, and product decisions across the organization.    This role sits at the intersection of graph analytics, identity resolution, and advanced forecasting. The Senior Lead  Data Scientist will   be responsible for   designing and   optimizing   graph-based representations of   Dynata's   data assets, developing predictive models that improve key business outcomes, and ensuring analytical models are robust, scalable, and production-ready.    Reporting to the VP, Data Science, this individual will partner closely with product, engineering, and platform teams to build capabilities supporting use cases such as identity resolution, feasibility prediction, panel health monitoring, audience intelligence, dynamic pricing, and operational optimization.    Key Responsibilities    Graph Science & Identity Intelligence     Architect and   optimize   graph-based data models supporting audience intelligence, project similarity analysis, clustering, and relationship-driven analytics.    Develop and   maintain   resilient identity resolution frameworks across multiple respondent identifier systems using deterministic and probabilistic matching techniques.    Design graph structures that support downstream analytics, forecasting, optimization, and AI applications.    Continuously evaluate graph performance, scalability, and business impact.    Forecasting & Predictive Modeling     Build and   maintain   forecasting models for supply prediction, incidence estimation,   completion   probability, panel health, and other business-critical use cases.    Develop time-series and predictive models that account for changing respondent behavior, market dynamics, and operational conditions.    Extend forecasting approaches to support scenario analysis, optimization, and decision support.    Monitor model performance and   identify   opportunities for continuous improvement.    Model Quality & Technical Leadership     Design and execute rigorous validation strategies to assess model accuracy, stability, scalability, and operational readiness.    Establish best practices for model evaluation, experimentation, monitoring, and governance.    Serve as a technical authority for graph analytics, forecasting methodologies, and production-grade machine learning.    Ensure solutions are designed for long-term maintainability, performance, and business value.    Cross-Functional Collaboration     Partner closely with Product, Technology, and Data Platform teams.    Collaborate on schema design, feature engineering strategies, and data contracts to ensure platform capabilities support analytical requirements.    Translate complex analytical findings into actionable business recommendations.    Influence technical and business stakeholders on…