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Misionero · Mexico City Metropolitan Area

Data Scientist - Supply Chain

Hybridentry_levelfull timePosted 3 days ago
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Stack mentioned

pythonsqlstatisticsexcelazurepandasnumpydata-sciencetime-seriesdata-governancedata-analysisdata-modelingpower-bi

About Misionero

Misionero is a forward-thinking produce company built on the principles of treating people with respect and balancing growth with quality. We specialize in high-quality leafy greens, organic salad staples, and value-added vegetables, maintaining a deep commitment to ethical growing, processing, and harvesting practices. As modern pioneers in the agro-industry, we focus on innovating and transforming the industry through new technologies and a collaborative environment to create real food for a greener future.

Harvest the Data

Misionero is leveraging a cloud data strategy to centralize and enhance its data assets and operations, creating an AI-ready infrastructure. This initiative combines our profound agricultural expertise with cutting-edge technology to enable stakeholders to access, analyze, and synthesize production data with speed and clarity.

Position Overview

We are seeking a talented Data Scientist to join our growing team with a focus on supply chain and operations. This role will focus on building scheduling, forecasting, and planning tools that directly support production decision-making — translating operational knowledge into systematic, data-driven systems that non-technical teams can use daily. The immediate priority is designing and deploying a production scheduling suite for our packing operation, with longer-term scope across demand forecasting, harvest planning, inventory strategy, and ERP systems implementation.

Core Responsibilities

• Design and build operational planning tools (scheduling, forecasting, inventory) that production and supply chain staff can operate independently.

• Develop demand forecasting models (short-term and long-term) to support production planning and raw material procurement.

• Translate data into actionable insights and communicate them to technical and non-technical stakeholders, including C-level suite.

• Ensure data quality and robust analytical practices.

• Support AI-driven and data-informed decision-making as part of our 2026 Data Strategy. Design and maintain dashboards and key metrics (KPIs) to monitor operational performance and identify improvement opportunities.

• Lead data science projects to determine, validate, and update key operational rules — using data rather than assumption to drive scheduling parameters, capacity targets, and cost drivers.

• Design analytical frameworks that define how multiple inputs drive business decisions under uncertainty (e.g., producing against unconfirmed demand).

• Partner with production planners, operations teams, and cross-functional stakeholders to capture domain knowledge and validate outputs.

Requirements

• Degree in Computer Science, Engineering, or Applied Mathematics.

• 3–5+ years of experience in Data Science, Analytics, or similar roles.

• Strong proficiency in Python for data manipulation, modeling, and automation.

• Experience working with SQL and structured datasets.

• Experience in statistical modeling, structured data analysis, and forecasting methods.

•Understanding of data quality and validation practices.

• Experience designing analytical methodologies for domains without established approaches.

• Bilingual Spanish/English.

• Strong Excel proficiency — advanced formulas, data modeling, dashboard design.

• Excel is a primary delivery platform for operational tools in this role. Experience working with cloud-based environments and BI tools. Microsoft ecosystem is a plus (Azure, Power BI).

• Some exposure to operations, supply chain, or manufacturing concepts (scheduling, capacity, inventory, perishable products). Deep domain expertise is not required — willingness to learn is.

Strongly Preferred

• Experience with optimization problems (scipy.optimize, OR-Tools, PuLP, or similar).

• Experience with demand forecasting or time-series modeling. • Pandas, numpy, Scikit-Learn.

• Familiarity with ERP systems or operational data sources.

• Experience with probabilistic modeling (Bayesian methods, PyMC, Stan or similar).

• Understanding of uncertainty and strategic thinking in decision-making showing strong business actionment.

• Experience building tools for non-technical end users — people who will use your output daily but won't modify your code.

Soft Skills

• Curiosity

• Proactivity

• Autonomy

• Teamwork

• Good communication (verbal & written)

• Detail orientation

• Problem solving

• Comfort working directly with operations teams — floor managers, production planners, field coordinators — not just data teams

What We Offer

• Competitive salary based on experience.

• Benefits in compliance with Mexican labor law.

• Hybrid work model: 2 days of home office per week.

• During the first 2 months (onboarding period): 1 day of home office per week.

• Periodic travel to US production facilities (California and Maryland).

• Exposure to strategic data initiatives aligned with our 2026 roadmap.

• 🌐 Ownership of high-impact projects — you will build the tools that drive daily production decisions for the company.

About this role: This is not a traditional data science position where you build models and hand off insights. You will own the end-to-end design, build, and deployment of tools that production teams use every day. The work is tangible — if your scheduling tool works well, the plant wastes less product and fills more orders. You will see the impact of your work on the production floor, not just in a dashboard. https://misionero.com

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