Experience

Farmers Alliance Companies

• United States
• Insurance
• 100 - 200 Employee

• Lead Data Scientist

  • Sep 2019 - Present

  - Created and implemented new metrics to track facility management operations and energy performance of 300 sites, resulting in a 15% reduction in energy consumption and a 20% improvement in building maintenance efficiency. - Successfully deployed and maintained data science solutions that handled large datasets (>1TB) with 99.9% uptime. - Worked with the software team for deployment of ML solutions in the CAFM platform. - Developed and tracked 10+ KPIs, providing actionable… Show more - Created and implemented new metrics to track facility management operations and energy performance of 300 sites, resulting in a 15% reduction in energy consumption and a 20% improvement in building maintenance efficiency. - Successfully deployed and maintained data science solutions that handled large datasets (>1TB) with 99.9% uptime. - Worked with the software team for deployment of ML solutions in the CAFM platform. - Developed and tracked 10+ KPIs, providing actionable insights to drive strategic decision-making and enhance performance. - Monitored and tracked performance metrics over a 12-month period, validating the success of implemented changes and identifying areas for further optimization. - Implemented process changes resulting in a 20% reduction in job completion time.- Created and implemented new metrics to track facility management operations and energy performance of 300 sites, resulting in a 15% reduction in energy consumption and a 20% improvement in building maintenance efficiency. - Successfully deployed and maintained data science solutions that handled large datasets (>1TB) with 99.9% uptime. - Worked with the software team for deployment of ML solutions in the CAFM platform. - Developed and tracked 10+ KPIs, providing actionable insights to drive strategic decision-making and enhance performance. - Monitored and tracked performance metrics over a 12-month period, validating the success of implemented changes and identifying areas for further optimization. - Implemented process changes resulting in a 20% reduction in job completion time. Skills: Machine Learning · Deep Learning · Data Science · Data Visualization · Python (Programming Language) · Tableau · SQL

• Data Engineer

  • Jun 2017 - Sep 2019

  Machine learning and deep learning in exploration and development geosciences projects - Created machine learning, deep learning workflows encompassing data gathering, pre-processing, model development, training, validation, hyper-parameter tuning and testing. - Implemented various supervised machine learning models such as K-Nearest Neighbors, SVM, DecisionTrees, and Random Forest for facies classification using well log data; created training, test data sets. Carried out cross… Show more Machine learning and deep learning in exploration and development geosciences projects - Created machine learning, deep learning workflows encompassing data gathering, pre-processing, model development, training, validation, hyper-parameter tuning and testing. - Implemented various supervised machine learning models such as K-Nearest Neighbors, SVM, DecisionTrees, and Random Forest for facies classification using well log data; created training, test data sets. Carried out cross validation. - Used neural networks on seismic multi-attribute transforms to predict log property from seismic data - Implemented Multiple linear regression and PCA for identification of the important seismic attributes for reservoir characterization - Used Convolutional Neural networks (CNN) for geological image classification on core and thin sections. Experimented with different deep learning architectures such as VGG, Resnet and hyperparameter optimization and tuning to obtain better resultsMachine learning and deep learning in exploration and development geosciences projects - Conducted predictive analysis using regression models for risk mitigation in well drilling - Created machine learning, deep learning workflows encompassing data gathering, pre-processing, model development, training, validation, hyper-parameter tuning and testing. - Implemented various supervised machine learning models such as K-Nearest Neighbors, SVM, DecisionTrees, and Random Forest for facies classification using well log data; created training, test data sets. Carried out cross validation. - Used neural networks on seismic multi-attribute transforms to predict log property from seismic data - Implemented Multiple linear regression and PCA for identification of the important seismic attributes for reservoir characterization - Used Convolutional Neural networks (CNN) for geological image classification on core and thin sections. Skills: Machine Learning · Deep Learning · Python (Programming Language)



Gallagher

• United States
• Insurance
• 700 & Above Employee

• Data Analyst

  • Feb 2014 - Apr 2017

  Subsurface data analysis | Data visualization - Applied statistical and machine learning, artificial intelligence for feature engineering, ranking and selection, sensitivity analysis, uncertainly analysis, production prediction and well design optimization using Python, R, and MATLAB - Well experienced developing Dashboards in Tableau and PowerBI - Worked closely with geologists, geophysicists, engineers and management to frame emergent problems, to evaluate public and proprietary… Show more Subsurface data analysis | Data visualization - Applied statistical and machine learning, artificial intelligence for feature engineering, ranking and selection, sensitivity analysis, uncertainly analysis, production prediction and well design optimization using Python, R, and MATLAB - Well experienced developing Dashboards in Tableau and PowerBI - Worked closely with geologists, geophysicists, engineers and management to frame emergent problems, to evaluate public and proprietary datasets, and to provide a variety of analytical solutions/tools - Python scripting to analyze processed seismic data – implemented various signal processing modules for seismic processing and analyses - Implemented seismic inversion algorithms such as colored inversion, model based inversion using Python Show less Subsurface data analysis | Data visualization - Applied statistical and machine learning, artificial intelligence for feature engineering, ranking and selection, sensitivity analysis, uncertainly analysis, production prediction and well design optimization using Python, R, and MATLAB - Well experienced developing Dashboards in Tableau and PowerBI - Worked closely with geologists, geophysicists, engineers and management to frame emergent problems, to evaluate public and proprietary… Show more Subsurface data analysis | Data visualization - Applied statistical and machine learning, artificial intelligence for feature engineering, ranking and selection, sensitivity analysis, uncertainly analysis, production prediction and well design optimization using Python, R, and MATLAB - Well experienced developing Dashboards in Tableau and PowerBI - Worked closely with geologists, geophysicists, engineers and management to frame emergent problems, to evaluate public and proprietary datasets, and to provide a variety of analytical solutions/tools - Python scripting to analyze processed seismic data – implemented various signal processing modules for seismic processing and analyses - Implemented seismic inversion algorithms such as colored inversion, model based inversion using Python Show less