7 дней назад
Senior Data Scientist (Consumer Analytics)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Scientist (Consumer Analytics): Working with large-scale consumer and behavioral datasets to improve measurement products through data validation, statistical methodologies, sampling approaches, and pipeline quality controls. Focus on designing scalable analytical approaches, investigating root causes of data issues, and validating production solutions across cloud-based data platforms.
Location: Bogota, Colombia; hybrid work
Company
Consumer intelligence company providing retail and consumer goods organizations with business intelligence, predictive analytics, and consumer buying behavior insights across more than 100 countries.
What you will do
- Work with large-scale consumer and behavioral datasets supporting measurement products used across North America.
- Evaluate and improve data preparation, validation, projection, and measurement methodologies.
- Design and prototype statistical and data-driven approaches for market and measurement challenges.
- Develop quality, validation, and performance indicators tied to product accuracy and reliability.
- Partner with Product, Engineering, and global Data Science teams to support production deployment.
- Investigate data issues, perform root-cause analysis, document methodologies, and communicate recommendations to technical and non-technical stakeholders.
Requirements
- 3–6 years of experience in data science, statistical analysis, or a similar hands-on analytics role.
- Strong foundation in statistics, mathematics, econometrics, or data science.
- Advanced Python proficiency for data manipulation, validation, and analysis.
- Strong SQL skills and experience querying large, complex datasets.
- Experience with data cleaning, validation, aggregation, quality control, cloud environments, and version control with Git.
- Experience with Azure and Databricks is preferred among cloud platforms; ability to explain technical concepts clearly and work independently.
Nice to have
- Experience with consumer, retail, CPG, panel, survey, or transactional data.
- Knowledge of projection methods, weighting, sampling, or measurement frameworks.
- Experience supporting product development or data products.
- Background in economics, statistics, or applied research.
- Familiarity with Spark or PySpark.
Culture & Benefits
- Flexible working environment.
- Volunteer time off.
- LinkedIn Learning.
- Employee Assistance Program.
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