[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 through powerful insights that drive client decisions. They are seeking a Senior Data Scientist I to design and build new measurement products, develop statistical and machine learning models, and collaborate with various teams to deliver custom solutions using Nielsen datasets.
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
- Company-provided vehicle if applicable
- Discretionary incentive/bonus eligibility if applicable
- Bonuses
- Equity
- Other incentives
Company Overview
Company H1B Sponsorship