Senior Data Scientist I

The Custom Media Analytics Delivery team sits within Nielsen's Commercial organization and functions as an incubator for new innovative products. We leverage existing Nielsen datasets to build custom solutions that don't yet exist in Nielsen's standard product portfolio. That means taking raw, often messy datasets from across Nielsen's ecosystem and turning them into something a client can actually use — which requires knowing the data deeply, modeling it correctly, and moving fast.What You'll DoDesign and build new measurement products by combining Nielsen datasets across National and Local linear TV, Streaming, Audio, and Digital — understanding the weighting rules, projection logic, and methodology differences that make cross-dataset work hard to get rightDevelop statistical and machine learning models that extend or adapt Nielsen methodologies to answer questions that standard products can't addressWrite production-quality SQL, Python, and PySpark to extract, transform, and model data fromNielsen's cloud data environmentBuild reusable data pipelines and ETL workflows that allow custom solutions to be delivered repeatably rather than rebuilt from scratch each timeUse AI tools actively — to validate models, accelerate pipeline development, stress-test logic, and compress the time between concept and deliveryTranslate stakeholder requests into well-scoped analytical problems, push back when the ask is unclear, and deliver with clear documentation of methodology and assumptionsCollaborate with Research, Commercial Sales, and Client Insights teams; communicate complex model decisions in plain languageNielsen & Media Research Knowledge3+ years working directly with Nielsen datasets (TAM, DAR/N1Ads, DCR, Audio, or similar) with hands-on knowledge of Nielsen's weighting, projection, and audience estimation methodologyProven ability to merge and reconcile multiple Nielsen data sources, navigating differences in sample design, universe estimates, and reporting conventionsSolid grasp of US media research fundamentals across Television, and DigitalData Science & ModelingAdvanced degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field5+ years in data science or analytical research roles, with a track record of delivering production-grade models — not just analysesStrong foundations in statistical modeling, sampling theory, weighting, and survey-based projections; comfortable with ML techniques where they fitEngineering & Technical StackExpert-level Python and SQL; strong PySpark for big data work in cloud environments (AWS preferred)Experience with Databricks for large-scale data processing and ML workflows; familiarity with warehouse-native ML (Databricks ML, Snowflake, or BigQuery ML) is a plusExperience building and maintaining ETL pipelines using Airflow or equivalent orchestration toolsFamiliarity with data warehousing concepts, cloud-native storage (Redshift, S3, or similar), and data engineering principlesAI Fluency — Required, Not OptionalActive daily use of AI tools (LLMs, copilot-style assistants) for code generation, model validation, documentation, and workflow acceleration — this is a core expectation of the roleExperience designing agentic AI workflows for automation — chaining tools, validation steps, and outputs to reduce manual effort on repeatable tasksComfortable evaluating where AI outputs need verification versus where they can be trusted; understands the limits as well as the leverageCommunication & DeliveryAbility to explain methodology decisions to non-technical stakeholders without oversimplifying the tradeoffsStrong documentation habits — methods, data dictionaries, and assumptions written up so others can reproduce and build on your workProficiency in Tableau, Spotfire, or equivalent visualization tools for QA and client-facing outputThis role is for someone who is energized by building things that don't exist yet, comfortable in ambiguity, and disciplined enough to get the methodology right the first time.Enabling your best to power a better media future.Holistic Rewards: We are committed to an inclusive benefits package that supports our employees and their families. This includes comprehensive health and wellness plans, a 401(k) with a Nielsen company match, and a generous paid time off policy. Depending on the role, additional benefits may include a company-provided vehicle and/or discretionary incentive/bonus eligibility.Compensation Transparency: The posted base salary range is a reasonable estimate that may be adjusted based on the final work location of the selected employee. Individual pay within the range is determined by factors such as experience, training, geography, certifications, and business needs. Beyond base salary, this role may be eligible for bonuses, equity, or other incentives.Nielsen makes hiring decisions without regard to disability status, protected veteran status, or membership in any other protected class.Please be a