[Remote] Senior Data Scientist I

Note: The job is a remote job and is open to candidates in USA. Nielsen is dedicated to powering a better media future by providing insights that drive client decisions. The Senior Data Scientist I will design and build new measurement products, develop statistical and machine learning models, and collaborate with various teams to translate stakeholder requests into analytical solutions.

Responsibilities

• Design 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 right
• Develop statistical and machine learning models that extend or adapt Nielsen methodologies to answer questions that standard products can't address
• Write production-quality SQL, Python, and PySpark to extract, transform, and model data from Nielsen's cloud data environment
• Build reusable data pipelines and ETL workflows that allow custom solutions to be delivered repeatably rather than rebuilt from scratch each time
• Use AI tools actively — to validate models, accelerate pipeline development, stress-test logic, and compress the time between concept and delivery
• Translate stakeholder requests into well-scoped analytical problems, push back when the ask is unclear, and deliver with clear documentation of methodology and assumptions
• Collaborate with Research, Commercial Sales, and Client Insights teams; communicate complex model decisions in plain language

Skills

• 3+ 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 methodology
• Proven ability to merge and reconcile multiple Nielsen data sources, navigating differences in sample design, universe estimates, and reporting conventions
• Solid grasp of US media research fundamentals across Television, and Digital
• Advanced degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field
• 5+ years in data science or analytical research roles, with a track record of delivering production-grade models — not just analyses
• Strong foundations in statistical modeling, sampling theory, weighting, and survey-based projections; comfortable with ML techniques where they fit
• Expert-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 plus
• Experience building and maintaining ETL pipelines using Airflow or equivalent orchestration tools
• Familiarity with data warehousing concepts, cloud-native storage (Redshift, S3, or similar), and data engineering principles
• Active 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 role
• Experience designing agentic AI workflows for automation — chaining tools, validation steps, and outputs to reduce manual effort on repeatable tasks
• Comfortable evaluating where AI outputs need verification versus where they can be trusted; understands the limits as well as the leverage
• Ability to explain methodology decisions to non-technical stakeholders without oversimplifying the tradeoffs
• Strong documentation habits — methods, data dictionaries, and assumptions written up so others can reproduce and build on your work
• Proficiency in Tableau, Spotfire, or equivalent visualization tools for QA and client-facing output

Benefits

• Comprehensive health and wellness plans
• A 401(k) with a Nielsen company match
• A generous paid time off policy
• Additional benefits may include a company-provided vehicle and/or discretionary incentive/bonus eligibility
• Bonuses, equity, or other incentives

Company Overview

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