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Lead Data Scientist
Job Description:
Job Description
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.
About the Role
In this role, you will contribute to the development and refinement of our data processing pipeline while shaping new analytical methodologies. You’ll grow from owning specific steps of the pipeline to becoming an expert across data cleaning, preparation, and rule validation, working fluently with Python and large datasets. You will also design new methods, translate them into clear specifications, and collaborate with engineering teams to ensure accurate and scalable implementation. Close coordination with stakeholders helps you understand their needs, gather requirements, and secure alignment. This position is ideal for someone who enjoys handson coding, improving data processes, and driving methodological innovation within a collaborative, crossfunctional environment.
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.
- Data Analysis Skills: Proficiency in manipulating, analyzing, and interpreting large data sets and experience presenting the findings and recommendations.
- Programming Proficiency: Experienced programming in Python, an ideal candidate has already implemented Statistical methods like outlier validation. Experience programming efficiently to process large amounts of data, optimally using the PySpark package. Optionally, experience in SQL and working with queries.
- Communication and Collaboration: Strong communication, writing, and collaboration skills. Experience or interest in supporting cross-functional stakeholders in production deployment
- Continuous Learning: Eagerness to adopt and develop evolving technologies and tools.
Nice to Have
- Statistical Expertise: Strong statistical and logical skills, with experience in data cleaning, outlier validation, sampling, bias reduction, indirect estimation, and data aggregation techniques.
- Software Engineering Skills: Knowledge in software engineering, including experience designing and developing software
- Technology Skills: Familiarity with technology stacks for cloud computing (AzureAI, Databricks, Snowflake), experience with version control systems GitHub or Bitbucket
Embark on this exciting journey to transform our panel measurement business and make a significant impact in the world of consumer analytics. Apply now to be a part of our innovative team!
Additional Information:
Our Benefits
- Flexible working environment
- Volunteer time off
- LinkedIn Learning
- Employee-Assistance-Program (EAP)
NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human r
