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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Lead Data Scientist, Graph & Forecasting - **Company:** Dynata LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $120,000.0 - $155,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Network Analysis, Cluster Analysis, Data Infrastructure, Decision Support Systems, Graph Database, Python (Programming Language), Machine Learning, Neo4j, Feature Engineering, Model Validation, Data Management, User Identification - **Published:** August 25, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18063316?backUrl=%2Fcareer%2F18063316%2FSenior-Lead-Data-Scientist-Graph-Forecasting ## About the Role * 8+ years of hands-on experience in data science, applied machine learning, analytics, or related fields. * Proven experience developing and deploying graph analytics, machine learning, or predictive modeling solutions in production environments. * Deep expertise in graph analytics, including graph databases, graph algorithms, similarity modeling, clustering, and network analysis. * Strong experience with graph technologies such as Neptune, Neo4j, TigerGraph, or comparable platforms. * Strong background in forecasting, time-series analysis, statistical modeling, and predictive analytics. * Advanced proficiency in Python and modern data science tooling. * Experience working with large-scale, noisy, real-world operational datasets. * Demonstrated ability to make complex technical decisions and operate effectively in ambiguous problem spaces. * Strong communication skills with the ability to explain complex analytical concepts to technical and non-technical stakeholders. * Experience collaborating with product,engineering,andplatformteams to deliver production-ready solutions., * Experience with identity resolution, entity resolution, master data management, or identity graph development. * Experience applying graph analytics to similarity modeling, community detection, clustering, relationship discovery, recommendation,andgraph embeddings. * Experience with forecasting, trend and seasonality detection, anomaly and change-point detection, cohort evolution, longitudinal measurement,anddemand planning,. * Experience in market research, panel data, audience measurement, advertising technology, marketplaces, or related industries. * Experience with cloud-native analytics and machine learning environments, including AWS ecosystem. * Familiarity with optimization, simulation, or decision-support systems. ## Description This role sits at the intersection of graph analytics, identity resolution, and advanced forecasting. The Senior LeadData 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 theVP,Data Science, this individual will partner closely withproduct,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., 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 analytical investments, priorities, and roadmap decisions. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Cyber Sleuth: Finding Hidden Connections in Cyber Data](https://www.wearedevelopers.com/videos/893-cyber-sleuth-finding-hidden-connections-in-cyber-data) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [Graphs and RAGs Everywhere... 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