NielsenIQ
consumer intelligence
LeadDataScientist
Neural analysis suggests this role is
optimal for mid candidates.
“Lead Data Scientist at NielsenIQ. Skills: Data Science, Python, statistics, mathematics, econometrics, panel data, software development, data analysis, cloud computing. solving complex client challenges. providing data-driven, actionable, timely, and innovative solutions”
What You'll Achieve.
make bold decisions and transform their businesses; drive innovation and growth; uncover the complete consumer journey for our clients; revolutionize the way we measure consumer behavior both online and in-store; build solutions that work end‑to‑end; transform our panel measurement business; make a significant impact in the world of consumer analytics
Industry & Context.
solving complex client challenges; statistical and data analytical methods; statistical and logical skills
What They're Looking For.
Must Have
Master’s / Doctorate Degree in Data Science, Mathematics, Statistics or BETech. Computer Engineering degree in Computer Science, Data Science or related fields involving statistical analysis of large data sets, Proficiency in manipulating, analyzing, and interpreting large data sets, Experienced programming in Python, Experience programming efficiently to process large amounts of data, communication, writing, and collaboration skills
Nice to Have
good understanding of consumer behavior, panel-based projections, and consumer metrics and analytics, successfully designed and developed software applying statistical and data analytical methods, demonstrated your ability to handle complex data sets, Experience with (un)managed crowdsourced panels and receipt capture methodologies, experience in SQL and working with queries, Experience or interest in supporting cross-functional stakeholders in production deployment, statistical and logical skills, with experience in data cleaning, outlier validation, sampling, bias reduction, indirect estimation, and data aggregation techniques, Knowledge in software engineering, including experience designing and developing software, Familiarity with technology stacks for cloud computing (AzureAI, Databricks, Snowflake), experience with version control systems GitHub or Bitbucket
What You'll Do.
solving complex client challenges
providing data-driven
and innovative solutions
developing innovative solutions that uncover the complete consumer journey for our clients
developing a tool that can simulate the impact of production process changes on client data
and interpreting large data sets
presenting the findings and recommendations
programming efficiently to process large amounts of data
How You'll Work.
Team & Collaboration
Join a dynamic and diverse global team; supporting cross-functional stakeholders in production deployment; collaboration skills
Communication Scope
communication; writing; collaboration skills
Full Job Description
Our NielsenIQ teams empower our clients to make bold decisions and transform their businesses in trusted data, solutions, and insights designed to drive innovation and growth. The NielsenIQ North America Data Science team is passionate about solving complex client challenges and providing data-driven, actionable, timely, and innovative solutions. Join a dynamic and diverse global team dedicated to developing innovative solutions that uncover the complete consumer journey for our clients. We are seeking a highly skilled Data Scientist with strong development skills in programming languages such as Python. Additionally, expertise in statistics, mathematics, econometrics, and experience with panel data to revolutionize the way we measure consumer behavior both online and in-store. Looking ahead, we are excited to find someone who will join our team in developing a tool that can simulate the impact of production process changes on client data. This tool outside of the production factory will allow the wider Data Science team to drive innovation with unpresented efficiency. ## Qualifications About You Ideally you possess a good understanding of consumer behavior, panel-based projections, and consumer metrics and analytics. You have successfully designed and developed software applying statistical and data analytical methods and demonstrated your ability to handle complex data sets. Experience with (un)managed crowdsourced panels and receipt capture methodologies is an advantage. - Educational Background: Master’s / Doctorate Degree in Data Science, Mathematics, Statistics or BE/BTech. Computer Engineering degree in Computer Science, Data Science or related fields involving statistical analysis of large data sets - End-to-End Mindset: Experienced understanding processes also holistically. You enjoy connecting methodology, engineering, and business context to build solutions that work end‑to‑end—spanning data ingestion, modeling, tooling, deployment, and impact evaluation.
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