Department: Science / Research & Innovation

Reports to: Director of Research Sciences

Location: San Francisco, CA / Berkeley (Hybrid schedule)

Base Salary Range: $65,000 to $85,000 annually

General Position Description

The Junior Data Scientist plays a key role in supporting AI and machine learning initiatives by building and maintaining data processing pipelines, training and validating models, and contributing to the development of deep learning solutions. This role involves working with PyTorch Lightning, applying best practices in model experimentation, and exploring a range of deep learning architectures, both current and historical. The position is ideal for someone eager to grow hands-on experience in regenerative agriculture and deep learning solutions while collaborating closely with a cross-functional teams of researchers, data scientists, and technology.

In this role, you’ll benefit from direct mentorship by experienced data scientists, meaningful exposure to real-world, high-impact projects, and the chance to grow your skills in a fast-moving, supportive environment. Whether you're experimenting with new modeling techniques or contributing to scalable solutions, you’ll be part of a team that values curiosity, collaboration, and continuous learning while being part of a team that values curiosity, collaboration, and continuous learning, all in service of creating a future with regenerative ingredients that nourish both people and the planet for generations to come.

Primary Job Responsibilities

Build, train, and evaluate deep learning models using PyTorch Lightning.
Design and implement data processing pipelines for structured and unstructured data, ensuring data quality and integrity throughout the workflow.
Apply and compare current and historical deep learning architectures to support sustainable solutions in agriculture.
Preprocess, clean, and analyze data to extract meaningful insights and prepare datasets for modeling
Collaborate with cross-functional teams to deliver actionable insights.
Document workflows, model architectures, and experimental results for reproducibility and knowledge sharing.
Present findings and recommendations to stakeholders using clear visualizations and reports

Key Competencies / Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
Experience with PyTorch Lightning for building and training deep learning models.
Understanding of deep learning architectures (e.g., CNNs, RNNs, transformers) and their application.
Familiarity with data processing pipelines: data collection, cleaning, transformation, and feature engineering.
Proficiency in Python and relevant libraries (NumPy, pandas, scikit-learn, PyTorch).
Knowledge of machine learning best practices such as model evaluation, cross-validation, and hyperparameter tuning.
Strong analytical and problem-solving skills.
Ability to communicate technical concepts to both technical and non-technical audiences.

Preferred Qualifications

Internship or project experience in data science or machine learning.
Exposure to cloud platforms (AWS, GCP) for data processing or model deployment.
Experience with data visualization tools (Matplotlib, Seaborn).
Knowledge of or experience with geospatial data.

Compensation, Perks & Incentives

Competitive base salary
Annual performance-based bonus
401 K Employer contribution
100% Employer paid health insurance for employee and family
Stock options

Employment Eligibility

Only applicants currently, and in the future will be, eligible to work in the United States will be considered for this position.

About Arva Intelligence

Arva is a machine learning software-based SaaS company with offices located in Houston, TX and Park City, UT. Arva's platform was built to apply our novel ML technology to the agricultural industry, optimizing and measuring regenerative practices, improving crop yields, and reducing operational costs for producers. Our platform helps our customers and partners capitalize on "natural regenerative practices" by providing recommendations that improve environmental and ecological ecosystems. Platform features include practice verification and registration, as well as the sale of environmental asset credits to our corporate buyers. Thus, Arva is helping to keep the planet green by providing a "green-tech" platform that informs, measures, validates, predicts, and registers carbon exchange opportunities, allowing growers and ranchers to produce and sell credits that are bought by our corporate partners, who endorse sustainable food supply and carbon neutrality.

This job description reflects the core duties of the role but is not intended to be all-inclusive. The role may evolve as the company grows, requiring additional responsibilities or changes in scope.

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