Senior Data Scientist

Senior Data Scientist

R26_0019273|CO

Avenida Calle 100 No. 9A-45, Bogota, Colombia

Employees work in a hybrid mode #LI- Hybrid

Company Description

NIQ, the world’s leading consumer intelligence company, reveals new pathways to growth for retailers and consumer goods manufacturers. With operations in more than 100 countries, NIQ delivers the most complete and clear understanding of consumer buying behavior through an advanced business intelligence platform with integrated predictive analytics. NIQ delivers the Full View.

NIQ was founded in 1923 and is an Advent International portfolio company. For more information, visit NIQ.com

We are looking for a hands-on Senior Data Scientist who enjoys working with large-scale consumer and retail datasets to solve complex measurement and analytics challenges. This role focuses on data quality, statistical methodologies, sampling approaches, and data pipeline validation , helping ensure the accuracy and reliability of products that support key business decisions.

You will work closely with data science, technology, and product teams to investigate data issues, design analytical approaches, validate outputs, and improve processes across cloud-based data platforms. This is not a traditional AI/ML modeling role . Instead, it is ideal for someone who enjoys working with complex, disaggregated datasets, applying statistical rigor, and building scalable solutions that directly impact consumer insights and product development.

If you are energized by solving ambiguous analytical problems, improving data reliability, and translating complex findings into actionable recommendations, this role is for you.

Responsibilities

Work hands‑on with large‑scale consumer and behavioral datasets , supporting measurement products used across North America; Evaluate existing data preparation, validation, and projection methodologies , identifying opportunities for improvement; Design and prototype new statistical or data‑driven approaches to address evolving market and measurement challenges; Develop end‑to‑end quality, validation, and performance indicators tied directly to product accuracy and reliability; Partner with Product, Engineering, and global Data Science teams to support production deployment of new solutions; Investigate data issues, perform root‑cause analysis, and recommend corrective actions; Clearly summarize findings and recommendations for technical and non‑technical stakeholders; Maintain clear documentation of methodologies, assumptions, and best practices

Requirements

3–6 years of experience in a Data Scientist, Statistical Analyst, or similar hands‑on analytics role; Strong foundation in statistics, mathematics, econometrics, or data science; Advanced proficiency in Python (data manipulation, validation, analysis — not just modeling); Strong working knowledge of SQL and experience querying large, complex datasets; Experience with data cleaning, validation, aggregation, and quality control at scale; Hands‑on experience in cloud environments , ideally Azure and Databricks; Experience working with version control (Git); Ability to explain technical concepts clearly and work independently with minimal supervision

Nice to have

Experience with consumer, retail, CPG, panel, survey, or transactional data; Exposure to projection methods, weighting, sampling, or measurement frameworks; Experience supporting product development or data products; Background in economics, statistics, or applied research; Familiarity with Spark / PySpark

Benefits

Flexible working environment; Volunteer time off; LinkedIn Learning; Employee-Assistance-Program (EAP)