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.

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 analytical investments, priorities, and roadmap decisions.

Qualifications

• 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, and platform teams to deliver production-ready solutions.

Preferred Qualifications

• 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, and graph embeddings.
• Experience with forecasting, trend and seasonality detection, anomaly and change-point detection, cohort evolution, longitudinal measurement, and demand 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.

Benefits

• A discretionary incentive program may be provided as part of the compensation package.
• Full range of medical and other benefits, dependent on full-time employment status.

Pay

The base salary range for this position is $120K–$155K/yr; however, base pay offered may vary depending on location, job-related knowledge, skills, and experience.

Dynata delivers the highest quality first-party data to help businesses gain precise insights, activate the right audiences, and confidently measure impact. With industry-leading respondent accuracy, reliability, and a commitment to continuous improvement, Dynata is the trusted foundation for smarter decision-making.