What are the responsibilities and job description for the Data/ML Scientist position at Seeds Renewables?
About us
Chloris Geospatial is a venture-backed technology company operating at the intersection of space-tech and nature-tech. Our mission is to accelerate the global transition to a net-zero and nature-positive economy with the most reliable, trustworthy and transparent natural capital data. Today we use industry-leading technology to measure the amount of carbon stored in terrestrial ecosystems.
About the role
As a Data / ML scientist, you will leverage your expertise in machine learning to build operational, scalable models that drive our commercial products. You will focus on applying advanced machine-learning techniques to solve complex problems and integrate data from multiple sources.
We are looking for someone with a strong background in machine learning, including experience with time series analysis, raster processing, and / or computer vision. Geospatial and remote sensing experience are a plus. You are creative and results-driven and know how to build and evaluate models that can be effectively deployed in production.
As a Data Scientist, you will use geospatial analytics and machine learning to build operational models that are the foundation of our commercial products. You have experience building models that combine data from multiple sources, and you understand geospatial data. Expertise in machine learning is essential, but experience and knowledge of time series, multivariate statistics, and Bayesian methods are also important. You are creative and you know how to build and evaluate high-quality models that can be deployed operationally. This position will report directly to the Chief Science Officer.
Responsibilities
- Develop and implement advanced machine learning models that map ecosystem properties (land cover, carbon density, biodiversity, etc.) and changes therein.
- Collaborate with a team of geospatial and remote sensing experts.
- Collaborate with software engineers to operationalize models you develop in a production environment.
- Create tools for model assessment and verification using robust statistical methods.
- Create tools that produce compelling visualizations of model results.
- Deploy models in operational environments and support their ongoing performance evaluation and optimization.
Qualifications
Location Time Commitment
This is a full-time position, requiring hybrid work from our Boston office two days / week.
Compensation
Competitive remuneration depending on experience and location. Benefits packages will be shared during the interview process.
We are also proud to be an equal opportunity employer that values diversity. We are excited to build a diverse and inclusive team and we encourage inquiries from talented and motivated applicants from all races, religions, colors, nationalities, genders, sexual orientations, ages, and disability groups. Come join us and help us build the future!
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