Senior Data Scientist I

Posted Yesterday
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Hiring Remotely in United States
Remote
Senior level
Digital Media • Information Technology • Analytics
The Role
Design and build custom measurement products by combining Nielsen datasets; develop statistical and ML models; write production-quality Python, SQL, and PySpark; build reusable ETL pipelines; use AI tools and agentic workflows; translate stakeholder requests into scoped analytical solutions; collaborate with Research, Sales, and Client Insights and document methodologies for reproducibility.
Summary Generated by Built In
Company Description

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.

Job Description

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 Do

  • 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

Qualifications

Nielsen & Media Research Knowledge

  • 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

Data Science & Modeling

  • 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
  • Engineering & Technical Stack
  • 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

AI Fluency — Required, Not Optional

  • 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

Communication & Delivery

  • 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

This 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.

 

#LI-LS1

Additional Information

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 aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels.

Skills Required

  • 3+ years working directly with Nielsen datasets (TAM, DAR/N1Ads, DCR, Audio, or similar)
  • Proven ability to merge and reconcile multiple Nielsen data sources, navigating sample design and reporting differences
  • Solid grasp of US media research fundamentals across Television and Digital
  • Advanced degree in Statistics, Mathematics, Computer Science, Data Science, or related quantitative field
  • 5+ years in data science or analytical research roles with production-grade model delivery
  • Strong foundations in statistical modeling, sampling theory, weighting, and survey-based projections; comfortable applying ML techniques
  • Expert-level Python and SQL
  • Strong PySpark experience for big data work in cloud environments
  • Experience with Databricks for large-scale data processing and ML workflows
  • Familiarity with warehouse-native ML (Databricks ML, Snowflake, or BigQuery ML)
  • Experience building and maintaining ETL pipelines using Airflow or equivalent orchestration tools
  • Familiarity with data warehousing concepts and cloud-native storage (Redshift, S3, or similar) and data engineering principles
  • Active daily use of AI tools (LLMs, copilot-style assistants) and experience designing agentic AI workflows
  • Ability to explain methodology to non-technical stakeholders and strong documentation habits
  • Proficiency in Tableau, Spotfire, or equivalent visualization tools for QA and client-facing output

Nielsen Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nielsen and has not been reviewed or approved by Nielsen.

  • Leave & Time Off Breadth Time off is described as generous, including flexible or unlimited PTO in some roles, paid holidays, sick days, volunteer time, and flex days. Personal days accrue monthly and can be used at employees’ discretion.
  • Parental & Family Support Support includes paid parental leave, family medical leave, adoption assistance, and adoption subsidies. These programs are positioned as part of a comprehensive package for families.
  • Strong & Reliable Incentives Select roles benefit from commissions, car pay, longevity bonuses, and performance-based bonuses. In some cases, overall compensation is characterized as outstanding or very satisfying.

Nielsen Insights

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The Company
HQ: New York, NY
30,034 Employees

What We Do

Nielsen shapes the world’s media and content as a global leader in audience insights, data and analytics. Through our understanding of people and their behaviors across all channels and platforms, we empower our clients with independent and actionable intelligence so they can connect and engage with their audiences—now and into the future. An S&P 500 company, Nielsen (NYSE: NLSN) operates around the world in more than 55 countries.

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