At Amini, we are committed to making a difference for our customers, colleagues, and communities. We are a dynamic, fast-growing deep tech startup. We are building environmental data infrastructure for Africa and the tropical belt. Amini is at the forefront of cutting-edge technology, utilizing Geospatial Data and AI / Machine Learning capabilities to solve environmental data scarcity for countries in the global south.
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Process ground truth and satellite-derived data for model training and validation.
Contribute to the training and development of geospatial machine learning models and analytics workflows.
Evaluate machine learning and statistical models for desired performance metrics.
Assess the quality and reliability of large-scale geospatial data products, such as land use/land cover (LULC) maps, weather, soil maps etc
Work closely with cross-functional teams to integrate models & analytic workflows into production.
Document and present technical findings to both technical and non-technical stakeholders.
Contribute expert insights to reports, case studies, and customer-oriented documents.
Assist in resolving customer-specific challenges related to geospatial data science.
What you will need
Bachelors Degree in a relevant field (STEM, Data Science, Computer Science, Geospatial Science, Statistics, Environmental Studies IT, etc.) or a related field. (Or graduating within a year)
Some experience in analyzing and interpreting large-scale geospatial data
In-depth Knowledge of data visualization, advanced analytics methods, tools, and programming languages and Data Science.
Familiarity with python and open-source geospatial libraries (e.g., GDAL/OGR, xarray, Geopandas, Shapely) and GIS tools like QGIS or ArcGIS
Knowledge and some experience of ML framework (Pytorch or TF etc..) knowledge and experience in Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs) - including techniques such as Retrieval-Augmented Generation (RAG) and Prompt Engineering - is highly desired.
Familiarity with machine learning tools and frameworks like Scikit-learn, Pytorch, TensorFlow etc.
Familiarity with cloud computing platforms (e.g., AWS, GCP) and Linux/Unix environments.
Ability to work independently and collaboratively within a globally distributed team.
Interest in New Technology, with critical thinking and a passion for cutting-edge data science algorithms,with a deep appreciation of the value and opportunities in predictive science and digital.
Excellent Collaboration and Communication Skills across all levels of seniority and multiple geographies.
Ability to Translate Complex Data into business-oriented value.
Proactive and Autonomous work ethic, capable of regularly dealing with ambiguity, complexity, and uncertainty
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