Note: The job is a remote job and is open to candidates in USA. Dynata is seeking a Senior Lead Data Scientist to develop predictive intelligence capabilities supporting operational, commercial, and product decisions. The role focuses on graph analytics, identity resolution, forecasting, and production-ready machine learning, while partnering with product, engineering, and platform teams to deliver analytical solutions.
Responsibilities
- 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
- 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
- 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
- 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
Skills
- 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
- 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
- Fully Remote
- A discretionary incentive program may be provided as part of the compensation package, dependent on full-time employment status.
- A full range of medical and other benefits, dependent on full-time employment status.
Company Overview
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