• Define and execute data science strategy aligned to business objectives and KPIs • Lead and mentor data scientists and analysts • Drive workforce transformation and modernization initiatives aligned with business strategy and operating model evolution • Establish modeling, analytics, and governance best practices • Design KPI frameworks for WF optimization, utilization, NPS, revenue and other operational metrics • Build and scale Power BI dashboards and reporting ecosystems • Deliver agentic AI solutions to automate workflows • Translate complex analytics into business insights for executives

• Own ML models end to end - frame the problem, write the design/RFC, build and train the model, ship it to a served endpoint and monitor its quality in production. • Build your model's training pipeline and package it for serving, deploying onto the shared platform Data Engineering builds and operates. • Own model quality, not the platform - you watch drift and performance and decide when to retrain. • Evaluate rigorously - experimental design, statistical validation, drift detection and retraining, champion-challenger evaluation and promotion. • Partner across the org - your model outputs feed the attributes/enrichment layer, payments risk, dashboards and client integrations, you'll collaborate with Data Engineering, backend, product and QA on contracts, deployment and rollout. • Move fast with AI-assisted development - we use it to accelerate implementation and experimentation, the highest-leverage contribution in this role comes from strong problem framing, system design, evaluation rigor and clear technical specifications.

• Design and build new measurement products by combining Nielsen datasets across TV, Streaming, Audio, and Digital • Develop statistical and machine learning models to answer questions not addressed by standard products • Write production-quality SQL, Python, and PySpark to extract, transform and model data • Build reusable data pipelines and ETL workflows for custom solutions • Use AI tools to validate models, accelerate pipeline development, and compress delivery time • Translate stakeholder requests into well-scoped analytical problems and deliver with clear documentation • Collaborate with Research, Commercial Sales, and Client Insights teams

• Own the data science and applied AI roadmap for operations—agentic systems, forecasting, lead scoring, voice of the customer aggregation, and decision-support that improve throughput, reliability, and unit economics. • Build agents and AI workflows that don't just predict but act. • Own the data science and AI behind post-sales product experiences, including the support agent, onboarding intelligence, and customer success automation—from design through production deployment, evaluation, and quality monitoring. • Lead, hire, and develop a data science team executing on operational and product-facing work; set standards for technical rigor, evaluation, and production quality. • Partner with operations, finance, and product leadership to identify high-leverage problems, frame them, and translate them into operational decisions and shipped AI capabilities. • Drive the full lifecycle from problem definition through deployment and monitoring, ensuring systems hold up in production—whether powering an internal forecast, an autonomous workflow, or a live customer interaction. • Establish metrics and evaluation frameworks connecting this work to operational, financial, and customer outcomes (e.g., deflection, resolution quality, time-to-value, retention), including rigorous evaluation of non-deterministic AI systems. • Collaborate with data engineering, machine learning engineering, platform, and product teams on the infrastructure, data quality, orchestration, tooling, and guardrails these systems depend on. • Communicate findings and recommendations to executive stakeholders, balancing technical depth with business clarity. • Champion an AI/agent-first way of working within the team—both as a hands-on technical leader (e.g., Claude Code) and by inventing agentic systems that make the team faster.