Geo-Data Scientist
- Data cleaning and preparation of data for geostatistical analysis using data science framework
- Performing exploratory data analysis and statistical interpretation of assay and composite data to support geological assessments and inform decision-making for resource modelling and evaluation processes using python data analytic tools
- Creating python scripts to automate resource modelling and estimation workflow
- Coding geological shapes (Ore Type, Lithology, Alterations) into block model and composite data to ensure accurate geological matching and interpretation during interpolation
- Performing variogram analysis to determine spatial correlation, continuity, and geological trends of deposits using PyGSLIB and resource modelling solutions platform (RMSP) python library. Create different variogram workflow based on data density within the district and domain of interest
- Performing resource grade interpolation using python to estimate and model the distribution of copper deposit within the Safford and Morenci district
- Performing reconciliation process between the long-range model and Short Range geologic reserve models to ensure consistency between the reserves estimated from both data
- Creating workflow to perform multivariate stochastic simulation tooptimize mine planning, drilling optimization, and ore routing decisions.
- Extracting, standardizing, and preprocessing datasets to ensure quality input for machine learning models.
- Engineered 1-D time series convolutional neural network to automate the identification of mineral phases in X-Ray diffraction data.
- Developing executable application for the deployment of machine learning models to automate mineral phase determination from X-ray diffraction (XRD) data.
- Designed and implemented GUI interfaces for dynamic visualization ofacid solubility and quick leach.
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
- Created python scripts to automate resource modelling and estimation workflow
- Performed variogram analysis to determine spatial correlation within the copper assay data using PyGSLIB and RMSP python library.
- Developed and presented 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.
- Developed approach to improve the team’s current modelling workflow
Data Analyst & Geologist Intern
- Created sample identification labels and submitting samples for laboratory analysis using computerized data transfer systems.
- Logged drill cuttings and drilled core samples to identify rock types, copper mineralization, alteration, and acid consumption
- Applied geostatistical algorithms and data analytic techniques to create block model for resource estimation and forecast modeling.
- Quantified 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%.