Principal Data Scientist
Company: Arable
Location: San Francisco
Posted on: April 7, 2025
Job Description:
Come work alongside some of the most talented minds in the
agtech industry. We are a team of innovators who are accelerating
the digitization and sustainability of our planet's food system. At
Arable, you will have the unique opportunity to build something
meaningful with an amazing group of people who care about each
other and their work.What we do:At Arable, our goal is to connect
all the world's farms to help optimize the global food system. This
is an ambitious goal, but the need has never been greater to
rethink how we will feed an ever-growing population and reduce our
impact on natural resources. We believe the heart of the solution
is digitizing the analog world with high-fidelity data to help food
producers optimize their operations. We hope the impact of our work
will improve the lives of farmers everywhere and be a major
contribution to securing the global food supply for decades to
come.A few examples of the work we're doing today:Helping farmers
in India and Mozambique adapt to the effects of climate change on
their farms with novel data-driven crop insuranceGiving produce
growers in California the tools to optimize production and minimize
wasteHelping irrigated farms in Nebraska manage water more
efficiently and sustainably to protect our water supplyWhat We're
Looking For:Arable Labs seeks an experienced and insightful
Principal Data Scientist to join our mission-driven team, reporting
to the Head of Data Science. Our work leverages unique,
high-fidelity field data to provide critical insights for global
agriculture and environmental monitoring. In this key role, you
will apply your deep expertise in machine learning, statistical
modeling, and software engineering to solve complex challenges in
agricultural water management. You will lead the development of
core predictive models, drive innovation through applied research,
and see your work contribute directly to farm sustainability and
resource efficiency, often supported by broader corporate
environmental initiatives. We need a hands-on technical leader
passionate about tackling meaningful problems and translating data
into real-world impact.Where You'll Make an Impact:
- Significantly improve models that help farmers optimize
irrigation, conserve water, and understand field conditions (e.g.,
rainfall, evapotranspiration, water balance).
- Advance Arable's predictive capabilities through the
application of novel ML techniques and sensor data analysis.
- Contribute directly to tools supporting climate resilience and
sustainable practices in agriculture.What You Will Do:
- Lead End-to-End Model Development: Drive the full lifecycle of
core machine learning models - from research, prototyping, and
validation to deployment (Python, Docker, Flask, AWS/SageMaker) and
ongoing performance monitoring and improvement. Key areas include
water balance, ET, rainfall, and irrigation insights.
- Conduct Applied Research & Innovation: Identify opportunities
and execute applied R&D projects to enhance model accuracy,
leverage new data sources (internal sensor streams, external
weather data), and develop novel predictive features, balancing
exploration with pragmatic delivery.
- Collaborate for Impact: Work closely with cross-functional
teams - Product (defining requirements, translating features),
Sensors/IoT (understanding data, calibration and validation), and
Software (API integration, production pipelines) - to ensure data
science solutions effectively meet business and user needs.
- Ensure Solution Quality & Provide Expertise: Uphold high
standards for model performance and data integrity through rigorous
validation, anomaly detection, and addressing operational
analytical needs. Serve as a subject matter expert in your domain
areas and contribute to the team's technical strategy and best
practices, potentially mentoring junior members.Required Experience
and Skills:
- MS or PhD in a quantitative field or equivalent deep practical
experience.
- 5-8+ years relevant hands-on experience developing & deploying
ML/DS solutions.
- ML & Statistical Depth: Strong theoretical understanding and
practical expertise in machine learning (especially time-series),
statistical modeling, and validation techniques.
- R&D Acumen: Demonstrated ability to conduct applied
research, tackle ambiguous problems, and deliver impactful,
data-driven solutions.
- Technical Implementation: Proficiency in Python for data
science (NumPy, pandas, scikit-learn, etc.), strong software
engineering practices (Git, testing, docs), and experience
deploying models via APIs (Flask) using containers (Docker) on
cloud platforms (AWS).
- Communication & Collaboration: Excellent ability to communicate
complex concepts clearly and collaborate effectively within a
cross-functional environment.Preferred Experience and Skills:
- Domain Knowledge: Background or strong interest in agriculture,
hydrology, meteorology, soil science, or related environmental
sciences.
- Sensor Data & Techniques: Experience with real-world IoT sensor
data (including CalVal), anomaly detection, and leveraging external
datasets (weather, geospatial).
- Startup Environment: Proven ability to thrive and take
ownership in a fast-paced, dynamic startup setting.
- AWS ML Ecosystem: Deep familiarity with AWS services,
particularly SageMaker.
- Mentoring: Experience guiding or mentoring other technical team
members.Location:United States based; SF Bay Area preferred, but
remote US is possible.What we offer:At Arable, you will be joining
a company of dedicated team players who bring together diverse
expertise and a passion for building a more sustainable future. We
are a fast-moving startup committed to providing a rewarding
employee experience through the work we do, the team, compensation,
and benefits, including:Excellent medical, dental, vision, and a
401k programFlexible PTOA focus on community involvement and career
developmentBeing a part of creating innovative new products that
have a positive impact on the worldAt Arable, we don't just accept
difference-we celebrate and support it. Not only because it's the
right thing to do but because we draw on the differences in who we
are, what we've experienced, and how we think to make Arable
thrive. Arable is proud to be an equal-opportunity workplace and is
an affirmative-action employer. We are committed to equal
employment opportunities regardless of race, color, ancestry,
religion, sex, national origin, sexual orientation, age,
citizenship, marital status, disability, gender identity, gender
expression, protected veteran status, and any other characteristic
protected under applicable State or Federal laws and
regulations.
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Keywords: Arable, Mountain View , Principal Data Scientist, Other , San Francisco, California
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