Senior Lead Data Scientist, Graph & Forecasting

🕒 August 24

🇺🇸 United States – Remote

💵 $120k - $155k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Dynata

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

💼 Consulting

📣 Marketing

☁️ SaaS

💰 $31.5M Debt Financing - Dynata on 2024-05

Consulting • Marketing • SaaS

Dynata is a market research and data company that provides high-quality first-party survey panels, audience data, and a suite of survey and analytics platforms to help organizations collect, activate, and measure insights. The company offers global B2B and B2C panels, survey scripting and fielding tools, data enrichment, audience activation, brand lift measurement, and data visualization, and it emphasizes data quality using AI/ML (QualityScore™) and security certifications. Dynata serves researchers, brands, media agencies, publishers, pollsters, and academics with both self-service and managed services.

📋 Description

• Lead development of predictive intelligence capabilities powering operational, commercial, and product decisions • Design and optimize graph-based representations of Dynata's data assets • Develop predictive models to improve key business outcomes • Ensure analytical models are robust, scalable, and production-ready • Partner with product, engineering, and platform teams on identity resolution, feasibility prediction, panel health monitoring, audience intelligence, dynamic pricing, and operational optimization • Architect and optimize graph-based data models for audience intelligence, project similarity analysis, clustering, and relationship-driven analytics • Develop and maintain resilient identity resolution frameworks using deterministic and probabilistic matching techniques • Design graph structures supporting downstream analytics, forecasting, optimization, and AI applications • 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 accounting for respondent behavior, market dynamics, and operational conditions • Extend forecasting approaches for scenario analysis, optimization, and decision support • Monitor model performance and identify continuous improvement opportunities • Design and execute validation strategies assessing accuracy, stability, scalability, and operational readiness • Establish best practices for model evaluation, experimentation, monitoring, and governance • Serve as technical authority for graph analytics, forecasting methodologies, and production-grade machine learning • Ensure solutions provide long-term maintainability, performance, and business value • Collaborate on schema design, feature engineering strategies, and data contracts • Translate complex analytical findings into actionable business recommendations • Influence stakeholders on analytical investments, priorities, and roadmap decisions

🎯 Requirements

• 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: Experience with identity resolution, entity resolution, master data management, or identity graph development • Preferred: Experience applying graph analytics to similarity modeling, community detection, clustering, relationship discovery, recommendation, and graph embeddings • Preferred: Experience with forecasting, trend and seasonality detection, anomaly and change-point detection, cohort evolution, longitudinal measurement, and demand planning • Preferred: Experience in market research, panel data, audience measurement, advertising technology, marketplaces, or related industries • Preferred: Experience with cloud-native analytics and machine learning environments, including AWS ecosystem • Preferred: 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 • Inclusive and accessible work environment • Accommodations available upon request for all aspects of the selection process

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