Data Scientist Interns (Machine Learning and Geospatial) at Amini

We are looking for a Geospatial Data Science Intern with expertise in data science and remote sensing. You will develop and deploy geospatial solutions across diverse environmental applications, including but not limited to agriculture, land use/land cover mapping, climate change monitoring, and natural resource management.

This internship will require you to leverage geospatial data science to tackle environmental challenges and facilitate data and AI-driven strategic decision-making.  You will be instrumental in generating insights through data management and analysis, you will play a key role in advancing our capabilities to address critical environmental challenges through innovative technology and developing statistical and AI/ML models based on current and historical data and enable scenario testing for predicted outcomes.

 The type of work you will be doing

• 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)
•  Hands-on experience in developing geospatial and machine learning models using satellite imagery.
• Some experience in analyzing and interpreting large-scale geospatial datas
• 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