Analista de Datos para la Optimización Agrícola (Remoto)

Placements24

Aguascalientes

Hybrid

MXN 300,000 - 540,000

Full time

39 hours ago
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Benefits offered by this job

Health coverage
Retirement plan
Performance incentives
Online courses & professional dev.
Paid time off

Job summary

Placements24 is seeking a Data Analyst for Agricultural Optimization to join a globally distributed, 100% remote team. You will analyze IoT, satellite, weather, and yield data to drive operational improvements and crop management decisions.

The ideal candidate has a strong quantitative background with Python/R, SQL, and visualization tools, and can translate complex data into actionable insights for agronomists and engineers.

Qualifications

  • Bachelor's or Master's in Statistics, Data Science, Computer Science, Agricultural Economics, or related field.
  • Experience as a Data Analyst, preferably with agricultural exposure.
  • Proficiency in Python or R (libraries like Pandas, NumPy, SciPy).
  • Experience with SQL for querying and management.
  • Data visualization skills (Tableau, Power BI, Matplotlib, Seaborn).
  • Understanding of statistical principles and modeling.
  • Familiarity with agricultural concepts is a plus.
  • Strong problem-solving and communication skills.
  • Independent work in a remote setup.

Responsibilities

  • Gather, process, and analyze large agricultural datasets from diverse sources.
  • Develop data models to identify patterns in crop performance, soil health, and environmental conditions.
  • Create visualizations and dashboards to communicate findings to stakeholders.
  • Build predictive models to forecast yields and optimize resource inputs.
  • Identify opportunities for operational improvements and cost reductions through data analysis.
  • Collaborate with product teams to inform AgTech solution design.
  • Ensure data accuracy, integrity, and security throughout analysis.
  • Stay updated on data analytics, ML, and agricultural tech trends.
  • Document methodologies, findings, and recommendations.
  • Provide ad-hoc data analysis support to various departments.

Skills

Data analysis
Python
SQL
Data visualization
Statistics

Education

Bachelor's or Master's degree

Tools

Tableau
Power BI
Pandas
NumPy
Matplotlib

Job description

About the Role

Our client, a forward-thinking agricultural technology firm, is seeking a skilled Analista de Datos para la Optimización Agrícola to join their globally distributed team. This is a 100% remote position, offering flexibility to work from anywhere in Mexico. The core purpose of this role is to leverage data analytics to enhance agricultural efficiency, sustainability, and profitability. You will work with diverse agricultural datasets, including IoT sensor data, satellite imagery, weather forecasts, and historical yield information, to identify key trends and develop data-driven recommendations. The ideal candidate possesses a strong quantitative background, proficiency in data analysis tools, and a keen interest in the agricultural sector. Your insights will help shape strategies for crop management, resource allocation, and operational improvements. You will collaborate closely with agronomists, farm managers, and software engineers to translate complex data into practical solutions that address real-world agricultural challenges.

Key Responsibilities
  • Gather, process, and analyze large and complex agricultural datasets from various sources.
  • Develop and maintain data models to identify patterns, correlations, and trends in crop performance, soil health, and environmental conditions.
  • Create compelling data visualizations and dashboards to communicate findings to stakeholders with varying levels of technical expertise.
  • Build predictive models to forecast crop yields, assess risks, and optimize resource inputs (water, fertilizer, energy).
  • Identify opportunities for operational improvements and cost reductions through data analysis.
  • Collaborate with the product development team to provide insights that inform the design of new AgTech solutions.
  • Ensure data accuracy, integrity, and security throughout the analytical process.
  • Stay abreast of the latest advancements in data analytics, machine learning, and agricultural technology.
  • Document analytical methodologies, findings, and recommendations.
  • Provide ad-hoc data analysis support to various departments as needed.
Requirements
  • Bachelor's or Master's degree in Statistics, Data Science, Computer Science, Agricultural Economics, or a related quantitative field.
  • Demonstrated experience as a Data Analyst, preferably with exposure to the agricultural industry or related scientific domains.
  • Proficiency in data analysis tools and programming languages such as Python (with libraries like Pandas, NumPy, SciPy) or R.
  • Experience with SQL for database querying and management.
  • Skills in data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
  • Understanding of statistical principles and modeling techniques.
  • Familiarity with agricultural concepts, such as crop cycles, soil types, and common farming practices, is a significant advantage.
  • Excellent problem-solving and critical thinking abilities.
  • Strong communication skills, with the ability to explain complex data insights clearly.
  • Must be highly organized, detail-oriented, and capable of working independently in a remote setup.
Benefits

This remote role comes with a competitive salary and a comprehensive benefits package, including health coverage, retirement savings options, and performance incentives. Our client fosters a culture of continuous learning, offering access to online courses, workshops, and professional development opportunities. You will be part of a dynamic and innovative company that is making a tangible impact on the future of farming. Enjoy the flexibility and autonomy of a remote work environment while contributing to cutting-edge agricultural solutions. We value work-life balance and provide ample paid time off. Join our mission to revolutionize agriculture through data.

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