Associate Analyst, Modelling
External
Nielseniq · Bogota, ColombiaPrepare for this interview
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Responsibilities
- Execute analyses error-free and on time.
- Manage execution of multiple analyses within project and work towards building efficiencies by identifying faster and simpler ways to improve the existing solutions
- Carry out multiple standard/non-standard analyses to help build quality and insightful proposals and final insights presentations.
- Gain a detailed understanding and develop expertise in existing analytical solutions
- Help in R&D studies by carrying out analyses as planned
- Advanced English level (B2 or C1) is a must
- From 6 months to maximum 3 years of experience in a data processing, transformation or modelling role (requirement)
- Advanced Excel level is a must for data analysis, and reporting.
- Intermediate Python proficiency is preferred
- Bachelor's degree in either of Statistics, Mathematics, Economics, or related
- MMM experience is a plus
- Candidate aware of the market research, FMCG/T&D industry is preferred.
- Thorough understanding and working knowledge of Statistical techniques like Regression, Data processing & pipeline operations.
- Hands on with data processing/programming tools R/Python/SQL/VBA/PowerBI
- Strong analytical and problem-solving skills with attention to detail.
Benefits
Additional Information
The Analyst will be involved in projects from a modelling perspective & Data transformation perspective. His/Her responsibilities will start from understanding project briefs from internal stakeholders, identify the right analytic solutions from product portfolio that will answer client questions, execute them error-free and deliver results on time. The work will be heavy on data extraction, processing, transformation, modelling, and finally presenting these from a business/non-technical point of view. As the person grows in experience, the profile will require that he/she starts carrying out the above tasks independently, contributing to building relationships with internal stakeholders, and improving our analytical solutions through R&D (Research & Development) initiatives and value-added insights.
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