Product Manager - Data and Derivative Products

Product Manager - Data and Derivative Products

This job is no longer open
The Company:
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.

The Role:
As a Product Manager - Data and Derivative Products, you will define our vision for geospatial imagery, other spatial datasets, and relevant non-spatial data to enable our customers and Descartes Labs scientists to derive new business and science insights related to exploration, safety, supply chain management, and sustainability. You will work with Engineering and our Science and Technology Solutions team to identify data requirements, survey and qualify potential sources, and prioritize the ingestion and transformation of those datasets. You will also work with Sales and directly with customers to identify opportunities to generate revenue from premium datasets and high value derivatives on the Descartes Labs Platform.

Your Impact

    • Explore, validate, and prioritize the ingestion of new datasets into the Descartes Labs Platform
    • Assist Descartes Labs scientists and support engineers in vetting and building the business case to acquire datasets for specific customer solutions and use cases
    • Collaborate with Engineering to define and maintain the dataset ingestion/enhancement roadmap
    • Identify high value derivative datasets to be added to the Descartes Labs Platform
    • Define strategies and execute tactics to achieve our premium dataset revenue targets
    • Maintain technical relationships with our commercial data providers
    • Manage our dataset budget

What You Bring

    • 4 years of experience in a product management, engineering, or science role
    • Graduate degree in remote sensing, image science, geospatial science, or geospatial intelligence with emphasis on the extraction of information from remotely sensed data
    • Solid understanding of geospatial and/or remote sensing technology, products, and data
    • Some familiarity with the application of machine learning methods to remotely sensed data
    • Some experience with programming or scripting languages, preferably Python

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 45-minute interview with the Hiring Manager
    • Next, candidates will be scheduled for a 45-minute interview with a member of the Product team
    • Finally, candidates will be scheduled for 3, 55-minute virtual interviews with cross-disciplinary stakeholders within the organization

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.
This job is no longer open
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