Senior Data Scientist
Arable
Data Science
Mexico City, Mexico
Posted on Nov 28, 2025
What We're Looking For:
Arable Labs is seeking a scientifically-minded and skilled Senior Data Scientist based in Mexico to join our globally distributed team. We are looking for an individual with a strong research background to apply deep expertise in machine learning, statistical analysis, and physics-based modeling to solve complex challenges in agricultural water management. Your work will focus on modeling atmospheric processes and field-level hydrology to deliver critical insights for farms. If you are passionate about applying your scientific skills to tangible environmental problems and thrive in a remote, collaborative setting, this role is for you.
What We Do:
At Arable, our mission is to accelerate the adoption of sustainable agriculture. Our integrated hardware-software solution empowers growers to make more informed decisions, manage resources like water sustainably, and adapt to climate change. We believe reliable, hyper-local data is the foundation for a more resilient and productive agricultural future.
Where You'll Make an Impact:
- Develop and improve spatio-temporal models of atmospheric processes to help farmers optimize water use for both pivot and flood irrigation systems.
- Advance Arable's predictive capabilities through the application of novel ML techniques and sensor data analysis.
- Contribute directly to tools that support climate resilience and sustainable water management practices in agriculture.
What You Will Do:
- Own End-to-End Model Development: Take ownership of the full lifecycle of predictive models, from research and prototyping to deployment and monitoring, using a blend of machine learning, statistical, and physics-based approaches.
- Execute Applied Research: Contribute to applied R&D projects to enhance model accuracy, leverage new data sources (including remote sensing and geospatial data), and develop novel predictive features.
- Collaborate for Impact: Work closely with our cross-functional teams in Product, Sensors, and Software to ensure data science solutions effectively meet user and business needs.
- Ensure Scientific Rigor: Uphold high standards for model performance and data integrity through rigorous validation and analysis, contributing to the team's technical best practices.
Experience and Skills:
- Required
- BS in a quantitative or scientific field (e.g., Physics, Atmospheric Science, Environmental Science, Engineering, Computer Science).
- 4+ years of hands-on experience developing and deploying data-driven models in a commercial or research setting.
- English Proficiency: Professional working proficiency in English (written and verbal) is required for collaboration in our globally distributed team.
- Modeling Depth: Strong expertise in building and validating predictive models using machine learning, statistical, or physics-based methods.
- Technical Implementation: Proficiency in Python for data science (e.g., pandas, NumPy, scikit-learn, SciPy), strong software engineering practices (Git, testing), and experience deploying models using containers (Docker) on cloud platforms (AWS).
- Global Collaboration: Proven ability to communicate and collaborate effectively in a highly distributed team across significant time zone differences.
- Preferred
- MS or PhD in a relevant scientific field.
- Domain Knowledge: Background in agronomy, hydrology, atmospheric science, or environmental science.
- Data Experience: Experience working with remote sensing, atmospheric, or geospatial datasets.
- Startup Environment: Ability to thrive and take ownership in a fast-paced, dynamic startup setting.
Location
Remote within Mexico. Travel to the US and other locations once per quarter at most.
What We Offer:
Join a dedicated team at Arable using cutting-edge technology to build a more sustainable future. We foster a culture of curiosity, impact, and collaboration.
- A competitive local compensation package.
- Comprehensive benefits in accordance with local standards.
- The flexibility of a remote work environment.
- The opportunity to see your work create a tangible positive impact for growers and the environment
- Our work creates a tangible positive impact for growers and the environment.