Data Analyst & Geologist Intern
- Data cleaning and preparation of data for geostatistical analysis using data science framework
- Statistical and Exploratory Data Analysis of copper assay data with python
- Creating python scripts to automate resource modelling and estimation workflow
- Performing variogram analysis to determine spatial correlation within the copper assay data using PyGSLIB and RMSP python library.
- Developing and presenting ideas to team lead and manager on how to implement machine learning in automating the classification of rock lithologies within the exploration and modelling workflow.
- Developing approach to improve the team’s current modelling workflow
Data Analyst & Geologist Intern
- Creating sample identification labels and submitting samples for laboratory analysis using computerized data transfer systems.
- Logging drill cuttings and drill core samples to identify rock types, copper mineralization, alteration, and acid consumption
- Applying geostatistical algorithms and data analytic techniques to create block model for resource estimation and forecast modeling.
- Quantifying uncertainty within the resource estimate using variogram analysis and multivariate transform simulation with python
Machine Learning Intern
- Setup machine learning framework/workflow for resource modeling team at Exodus dry mine, Nevada Gold Mines.
- Optimized rock classification workflow by developing rock classification system using convolutional neural network algorithm. This improves time used for manual classification by 80%.
- Designed and deployed the model via a web application using streamlit. Web-App Demo
- Incorporated geochemical data to understand and translate complex business problems into machine learning problems.
- Documented step by step procedure used in developing rock classification system in the SOP delivered to the Mineral Resource Team.
- Working on object recognition using tensorflow to further identify sub-rock types within some geological core boxes.
Data Scientist Intern
- Identified, analyzed and interpreted trends in complex data sets using supervised and unsupervised learning techniques.
- Used Python to manage, analyze, and visualize large data sets.
- Built machine learning model using linear regression and support vector machine with an 80% accuracy to predict customer’s reaction on the new product to be released by one of the company’s client.
- Applied appropriate data science techniques to develop an insurance prediction system (95% accuracy) that predicts the best policies for individual clients.
Geospatial Data Analyst
- Created and deployed an enterprise GIS system for the company using Geoserver, apache Tomcat, PostGres, and Ngrok tunneling
- Used GIS analytic tools to develop an eMarketing tool which was a channel for marketing the company’s product. This increased sales by 60%
- Analyzed transactions to build logical business intelligence model for real-time reporting
- Developed a geolocation and suitability map to help access the performance of a client product within the states of
- Carried out a GIS-Based suitability analysis for a telecommunication company using multi-criteria decision analytic tools. The suitability map produced was implemented in strategic locations by the client. This improved the quality of services delivered in the location by 80%.