Data Scientist

hace 7 días

Juárez Juárez Chih, México Wizeline A tiempo completo

Data Scientist – Supply Chain Industry
a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.
Data Scientist
In this role, you will work on high-impact initiatives involving demand forecasting, inventory optimization, and logistics analytics. You will partner closely with business and operations teams to transform data into actionable insights that improve end-to-end supply chain performance.
Office:
Hybrid — 1 day per week onsite / 4 days remote
Apply advanced analytics, statistical modeling, and machine learning to solve complex supply chain problems such as demand forecasting, inventory optimization, resource allocation, and logistics network analysis.
Design, develop, and maintain end-to-end data science solutions, from data exploration and feature engineering to model deployment and monitoring.
Build and optimize data pipelines and analytical workflows using
Azure Databricks
Translate business questions from sales, logistics, and operations teams into quantitative, actionable analyses.
Validate hypotheses, identify patterns, and design data-driven solutions that improve key supply chain KPIs.
Continuously evaluate data quality, analytical processes, and tooling, proposing improvements where needed.
Bachelor's Degree
in Data Science, Statistics, Engineering, Mathematics, Computer Science, or a related field.
~in Data Science, Analytics Engineering, or similar roles.
~ Python
SQL
, including experience with data science and ML libraries such as
Pandas, PySpark, Scikit-learn, and MLflow
.
~ large-scale datasets and pipelines in Azure Databricks
.
~ Solid understanding of statistical modeling, time series analysis, clustering, optimization, or simulation techniques.
~ demand planning, inventory management, logistics, or routing
Ability to work autonomously, owning projects end-to-end and making informed decisions with minimal supervision.
~ English level: Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Exposure to cloud-based data architectures beyond Azure (e.g., AWS, GCP).
Commitment to Professional Development
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