Data Scientist & Analytics Engineer - Forecasting Pipelines

Mondelez International; Thames; Híbrido; ARS 1.200.000 - 1.800.000; Jornada completa

Descripción de la vacante

Mondelēz International in Thames, Argentina seeks a Data Scientist Specialist to drive data initiatives and maintain data pipelines for forecasting and analytics. You will operationalize data processes and ensure secure, accessible data assets across the organization.

The role requires strong technical skills in data manipulation, statistical modeling, and cross-functional collaboration to improve forecast accuracy and data science capabilities.

Formación

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related quantitative field.
• 5+ years of experience in data analysis, business intelligence, or junior data science roles.
• Proficiency in Python or R for data manipulation and modeling; strong SQL skills.
• Experience with data visualization tools (Tableau, Power BI) and forecasting tools is a plus.

Responsabilidades

• Execute demand and supply segmentation, generate statistical forecasts, and maintain data science tools and systems.
• Build and maintain data pipelines and data transports for applicable datasets.
• Automate data workflows to produce visuals and ensure data accessibility and security.

Conocimientos

Data analysis

Data manipulation

Communication

Problem solving

Educación

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related quantitative field

Herramientas

Python

R

SQL

Tableau

Power BI

Pandas

NumPy

Scikit-learn

Descripción del empleo

Mondelēz International in Thames, Argentina seeks a Data Scientist Specialist to drive data initiatives and maintain data pipelines for forecasting and analytics. You will operationalize data processes and ensure secure, accessible data assets across the organization.

The role requires strong technical skills in data manipulation, statistical modeling, and cross-functional collaboration to improve forecast accuracy and data science capabilities.