Applied Scientist - Geospatial
Science and Technology Solutions /
Descartes Labs is a geospatial intelligence company with science and technology at its core. Launching out of Los Alamos National Laboratory in 2014, we build models of the earth to power the analysis of the world's largest physical systems. Our data science and software solutions create new sources of operational advantage for Agriculture, Consumer Packaged Goods, Mining, and Government.
Descartes Labs is proud to be a remote-first, deliberately distributed organization that recognizes that people have different needs and motivations for building a life and career that matters and works for them. For this reason, we are open to our employees working from any location, in a way that enhances their well-being, productivity, and role. We focus on helping our employees produce positive outcomes and we recognize that the path to getting there will look different for different people.
As an Applied Scientist you should have a passion for creating client value, cutting edge technology, the world of big data, and the connectivity of the physical and digital worlds with markets and business. Descartes Labs is building the geospatial data platform of the future that enables world class analysis at global scale. In this position, you will work with our internal data science team to build cutting edge solutions for business users across many industries. You will be an advocate for our technology and help transform the way our customers utilize geospatial data in their companies in ways entirely novel to them and the business world in general.
- Use our archive of satellite imagery, geophysical data, and other geospatial datasets to develop and implement scalable mineral exploration techniques and safety risk models
- Build and maintain operational dashboards and web applications to enable non-technical users to leverage the complex models we build
- Collaborate with product managers to develop new products and capabilities relevant to the mining sector
- Work with solutions managers to communicate progress to clients and translate the results of scientific analyses into actionable insights
- Actively participate as a member of a cross-disciplinary team, openly communicating your ideas, insights, and feedback and helping to continuously improve processes
What You Bring
- BSc, MSc, or PhD in a relevant scientific or quantitative field (e.g. remote sensing, imaging science, geography, geoscience)
- Demonstrated background developing statistical, machine learning, and/or simulation models for geospatial problems
- Proficiency in scientific computing with Python, with the ability to quickly pick up new technical skills
- Familiarity with dashboarding or web app development with Flask, Voila, Streamlit, Plotly, Panel, or other frameworks within the Python ecosystem
- Experience working with remote sensing and geospatial data
- Strong problem solving skills, with the ability to research, develop, and implement solutions to novel problems
- Self-motivated and able to work independently as well as within a team
Who You Are
- Curious. You are always exploring and experimenting, interested in why and how, seeking not only to understand but to make work and the world better. You enthusiastically share your learning with others and actively seek information and knowledge.
- Conscientious. You are determined, always keep your promises, and are forward thinking. Principled and integrous, you take your commitments seriously.
- Humble. Unpretentious and self-aware, you cultivate compassion for others and take responsibility for your mistakes. Egos are barriers to doing the best work and always learning.
- Open and Inclusive. You are receptive and interested in new ideas and perspectives, even when those perspectives don’t agree with your views. You value and respect difference and create ways for all people to contribute to the organization.
- Collaborative. You know it takes a team to get anything accomplished and you actively and inclusively work across the organization. You listen intently and openly and are always focused first on creating the best results.
- Adaptable. You are able to navigate changing circumstances and environments with ease and approach uncertainty with enthusiasm, while inspiring others towards effective goal setting and accomplishment.
Our Interview Process
- Qualified candidates will be invited to schedule a 45-minute interview with one of our recruiters
- Depending on the outcome of the recruiting interview, candidates will be invited to schedule a 30-60 minute interview with our Exploration and Safety Hiring Manager
- Next is a coding interview with a scientist from the Applied Science team
- Finally, candidates are invited to a round of virtual interviews with 4 members of the Science and Technology Solutions team
Top Reasons to Work at Descartes Labs
- We pride collaboration over ownership, iteration over perfection, principles over rules, and discussion over directives
- We’re using the world’s top technology to solve the world’s largest problems with a strong focus on sustainability, environment, and impact science
- We look at Descartes Labs as a work environment where people are included, treat their colleagues with professional regard and respect, and thrive as a result
- We’re a highly collaborative company that constantly promotes success through teamwork
- We strongly encourage and enjoy a flexible work environment
- Descartes Labs offers a generous compensation package including competitive salary; choice of medical plan; dental, life, and disability insurance; a 401K plan; paid holidays and paid time off
You belong here! Nobody checks every box and if your experience and interests match some of the above, we want you to apply.
Descartes Labs is committed to building a diverse community, where employees feel they belong, even if they are different. Scientific discovery is in our DNA and the more inclusive we are, the better our work will be; diversity fuels innovation!
Accommodations will be provided as requested by candidates during all aspects of our interview process.