Senior Data Scientist

Arable; Castilla-La Mancha; A distancia; EUR 51.000 - 70.000; Jornada completa

Descripción de la vacante

A leading ag-tech company is seeking a Senior Data Scientist to apply expertise in machine learning and statistical analysis. This remote role focuses on modeling atmospheric processes for sustainable agriculture. The ideal candidate has a BS in a quantitative field and 4+ years of experience in data-driven model development. You will work in a collaborative environment, delivering critical insights to support water management. Competitive compensation and benefits are provided.

Servicios

Competitive local compensation package

Comprehensive benefits

Flexibility of a remote work environment

Formación

• 4+ years of hands-on experience developing and deploying data-driven models.
• Professional working proficiency in English.
• Strong expertise in building and validating predictive models.

Responsabilidades

• Own the full lifecycle of predictive models from research to monitoring.
• Contribute to applied R&D projects to enhance model accuracy.
• Collaborate with cross-functional teams to ensure effective data science solutions.
• Uphold high standards for model performance and data integrity.

Conocimientos

Machine learning

Statistical analysis

Physics-based modeling

Python for data science

Effective communication

Technical implementation

Educación

BS in a quantitative or scientific field

MS or PhD in a relevant scientific field

Herramientas

Pandas

NumPy

scikit-learn

SciPy

Docker

AWS

Descripción del empleo

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:

• 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.