Data Scientist

Key Skills

Analytical and Problem solving, Databricks, Jupyter Notebook, Python Programming, Spark Core, SQL

Job Description

OUR MISSION

Mineral’s mission is to discover the intelligence of plantkind to feed and protect humankind. Our technology embraces the complexity of nature, unlocking agriculture data so the world can reimagine sustainable food production. This means leveraging advanced technology and use of AI across the total plant ecosystem to turn complex data into understandings that enable greater efficiency, productivity and sustainability.

Agriculture background preferred but not required — just the curiosity and passion to learn. If you are excited to make a difference in global food production and help work toward a more sustainable future for agriculture, we’d love to talk with you.

The Role:

Location: US (Remote), travel to Mountain View, CA at most 1 week per month (more initially).

This is an opportunity to combine your agronomic understanding with your passion for data science modeling to understand how well our perception models work in the real-world. You'll be working on projects at the intersection of agriculture, big data and AI. You'll partner with our modeling team who train, validate, and deploy perception models in production agriculture environments. You'll partner with our MLOps Data team who are collecting the data & images, from diverse locations & times of the year, and labeling them for model training. You'll take responsibility for pressure testing our understanding of model performance in the real-world, design experiments that identify any gaps in performance, and find creative solutions to bridge those gaps. You’ll have the opportunity to problem solve and be a part of the development of products that transform this space.

If you are a Data Scientist with a passion and experience in agriculture, and are excited to make a difference in global food production and climate change, we’d love to talk with you.

How you will make an impact:

• Work closely with software engineers & data engineers to ensure our models perform to the highest standard when deployed to real world production environments.
• Work with cross-functional internal / external stakeholders including MLOps, Engineering and Product to support a broad spectrum of agronomy experiments.
• Develop an ambitious yet practical roadmap for evaluating the qualities of models that underpin breakthrough technologies in agriculture.
• Design and coordinate tests of model performance - from in-field tests, exploratory unsupervised evaluations, as well as whole of system reviews of performance.
• “Roll up your sleeves” and get stuff done as a member of our core Science team.

What you should have:

• BSc in Data Science / Statistics / Math or equivalent experience
• 6+ years of professional agriculture experience
• Deep understanding & experience working with statistical & machine learning models, in connection with perception models and computer vision in an agricultural setting.
• Proficiency in supervised & unsupervised machine learning methods within Python, notebooks, & SQL for working with & interrogating large collections of labeled images
• Strong written and verbal presentation skills
• Demonstrated ability to self-manage, take initiative, problem-solve, and navigate through ambiguity
• Curiosity, humility and eagerness to learn

It would be great if you also had these:

• Masters Degree in agronomy, weed science, food engineering, or data science
• Experience with Databricks / Spark, or Apache Beam
• Experience with farming and agricultural equipment
• Experience in a startup environment
• Startup experience, or equivalent experience on early stage software teams

The US base salary range for this full-time position is $146,000 - $224,500 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google

At Mineral, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.