Senior Principal Data Scientist
2022 - PRESENTNielsenIQ- Contributed to various advanced analytics projects related to geospatial data analytics projects, route-to-market, and precision.
- Implemented a novel method for sales distribution using the linear optimization technique.
- Implemented parallel programming for various existing codes to increase the efficiency of the current methods.
Technologies: Amazon Web Services (AWS), Geospatial Data, Geospatial Analytics, Python, SQL, PySpark, GIS, Parallel Programming, Spark, ETL, Apache Spark, Data Engineering, Pandas, Data Wrangling, Datasets, MatplotlibMachine Learning Engineer and Data Scientist
2020 - PRESENTCenovus Energy- Developed several ML algorithms and shiny apps deployed to RS-connect, including a deep learning model to classify valid DTS shut-in, linear failure analysis, and predictions of the depth of geological formations using CNN.
- Supervised a data science co-op student on various projects.
- Co-supervised a master's student at the University of Alberta on using ML methods to predict spatial continuity parameters from data.
Technologies: Azure, Databricks, PySpark, Computer Vision, Python, SQL, NoSQL, MongoDB, Facial Recognition, Keras, Convolutional Neural Networks, Object Detection, Cloud Infrastructure, Natural Language Processing (NLP), Artificial Intelligence (AI), Machine Learning, Visual Basic for Applications (VBA), Linear Regression, Linear Optimization, Parallel Programming, Git, Scikit-learn, GeoPandas, Geology, TkInter, AutoML, TensorFlow, Algorithms, Data Science, Cloud, Neural Networks, ETL, Apache Spark, Data Engineering, Image Processing, 3D Image Processing, Pandas, Docker, Data Wrangling, Datasets, Simulations, Physics Simulations, User Interface (UI), Matplotlib, GitHub, 3DGeo-statistician and Machine Learning Engineer
2012 - 2020Husky Energy- Developed several predictive models for subsurface data using classical machine learning algorithms and a deep learning framework.
- Filed two patents—one has been granted, and the second is in process.
- Led a team of four technical individuals to develop a framework and a dashboard for resource estimation and prediction.
- Built 3D numerical models to characterize reservoir and uncertainty analysis.
- Taught several machine learning courses in the company.
- Received the best presentation award at the Husky tech forum. Presented three new workflows and ML models on subsurface data.
Technologies: Python 3, R, TensorFlow, Azure, PySpark, PyTorch, Python, SQL, Facial Recognition, Keras, Convolutional Neural Networks, Object Detection, Amazon Web Services (AWS), Cloud Infrastructure, Google Cloud Platform (GCP), Natural Language Processing (NLP), Artificial Intelligence (AI), Machine Learning, Visual Basic for Applications (VBA), Linear Regression, Linear Optimization, Parallel Programming, Git, Scikit-learn, GeoPandas, Geology, TkInter, Computer Vision, Algorithms, Data Science, Team Leadership, Cloud, Neural Networks, Pandas, Data Wrangling, Datasets, Simulations, Physics Simulations, User Interface (UI), GitHub, 3DResearch Assistant
2007 - 2012University of Alberta- Developed a novel workflow to measure geological uncertainty at long-term production optimization and published several papers on this subject.
- Published several peer-reviewed and conference papers about geostatistical methods in mining and oil and gas engineering.
- Acted as a teacher assistant in a few university courses, including reserve estimation methods.
- Acted as a software developer for Newmont Mining Corp, Denver, USA.
Technologies: Research, Programming, R, MATLAB, Python, Fortran, Data Science, Geology, Engineering, Linear Programming, Parallel Programming, Algorithms, Pandas, Algebra, Convex Optimization, Optimization Algorithms, Data Wrangling, Datasets, Simulations, Physics Simulations