Data Scientist – Python - Supply Chain

Data Scientist – Python - Supply Chain (Hybrid, Mexico City)

Location: Mexico City, Mexico – Hybrid (3 days onsite, 2 days remote)

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We are:

Wizeline, 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.

With the right people and the right ideas, there’s no limit to what we can achieve.

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Are you a fit?

Sounds exciting, right? Now, let’s make sure you’re a good match for this role:

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Key Responsibilities

• Build end-to-end data science solutions, from data exploration and feature engineering to model development, validation, and deployment.

• Analyze large-scale datasets and develop advanced analytical models to support forecasting, inventory optimization, resource allocation, and logistics planning.

• Translate complex business questions across sales, operations, logistics, and supply chain into actionable quantitative insights.

• Design, implement, and optimize ML pipelines using Azure Databricks and other modern data platforms.

• Collaborate closely with cross-functional teams—including Supply Chain, Finance, and Sales—to deliver insights and data-driven recommendations.

• Validate hypotheses, identify patterns, and develop analytical solutions that enhance supply chain performance and key metrics.

• Communicate clearly with non-technical stakeholders, explaining models, assumptions, and outcomes in a simple, business-friendly way.

• Document workflows, share knowledge with the analytics team, and contribute to continuous improvement of tools, methodology, and data quality.

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Must-have Skills (3–5+ years of experience)

• Strong hands-on experience in Data Science, Analytics Engineering, or similar analytical roles.

• Proficiency in Python, SQL, and ML/analytics libraries such as Pandas, PySpark, Scikit-learn, MLflow.

• Experience working with large datasets and building pipelines in Azure Databricks or similar cloud environments.

• Solid understanding of statistical modeling, time series forecasting, clustering, optimization, or simulation.

• Experience solving supply-chain-related problems such as demand forecasting, inventory optimization, or route planning (nice-to-have but highly valued).

• Ability to translate business needs into quantitative models and insights.

• Proven experience managing projects end-to-end with strong ownership and autonomy.

• Strong analytical mindset and comfort working with ambiguity in complex problem spaces.

• Excellent communication skills to present insights to non-technical stakeholders.

• Ability to work in dynamic environments with shifting priorities and multiple simultaneous projects.

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Nice-to-have

• Experience in the consumer goods, logistics, manufacturing, or supply chain domains.

• Familiarity with optimization techniques (linear programming, OR), simulation tools, or advanced forecasting methodologies.

• Experience designing analytics solutions that integrate with operational systems.

• Curiosity-driven mindset with interest in experimentation, research, and continuous learning.

• Experience collaborating with multidisciplinary teams (Supply, Ops, Finance, Sales).

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AI Tooling Proficiency

Leverage one or more AI tools to optimize and augment day-to-day work, including research, documentation, data exploration, and model experimentation. Provide recommendations on effective AI use and identify opportunities to streamline analytical workflows.

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What we offer

• A High-Impact Environment

• Commitment to Professional Development

• Flexible and Collaborative Culture

• Global Opportunities

• Vibrant Community

• Total Rewards

Specific benefits are determined by employment type and location.

Find out more about our culture here