Gabriel Ohaike
Machine Learning Engineer | Data Scientist at Filos Technology- Claim this Profile
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Topline Score
Bio
LinkedIn User
Gabriel is an excellent scholar. We have partnered on final projects for two classes at UC Berkeley MIDS program and I was impressed by his commitment, knowledge, hard work and professionalism. He would give his critical opinion on the subject matter, would volunteer to take on challenging tasks on the projects and deliver those ahead of or on time. On recent coursework, Machine Learning at Scale, Gabriel took on the task to build machine learning model for the project, run various iterations of multiple algorithms leading to the final model of choice, including detailed hyper-parameter tuning. I would recommend him in any Data Scientist position and would love to collaborate again in future.
LinkedIn User
Gabriel is an excellent scholar. We have partnered on final projects for two classes at UC Berkeley MIDS program and I was impressed by his commitment, knowledge, hard work and professionalism. He would give his critical opinion on the subject matter, would volunteer to take on challenging tasks on the projects and deliver those ahead of or on time. On recent coursework, Machine Learning at Scale, Gabriel took on the task to build machine learning model for the project, run various iterations of multiple algorithms leading to the final model of choice, including detailed hyper-parameter tuning. I would recommend him in any Data Scientist position and would love to collaborate again in future.
LinkedIn User
Gabriel is an excellent scholar. We have partnered on final projects for two classes at UC Berkeley MIDS program and I was impressed by his commitment, knowledge, hard work and professionalism. He would give his critical opinion on the subject matter, would volunteer to take on challenging tasks on the projects and deliver those ahead of or on time. On recent coursework, Machine Learning at Scale, Gabriel took on the task to build machine learning model for the project, run various iterations of multiple algorithms leading to the final model of choice, including detailed hyper-parameter tuning. I would recommend him in any Data Scientist position and would love to collaborate again in future.
LinkedIn User
Gabriel is an excellent scholar. We have partnered on final projects for two classes at UC Berkeley MIDS program and I was impressed by his commitment, knowledge, hard work and professionalism. He would give his critical opinion on the subject matter, would volunteer to take on challenging tasks on the projects and deliver those ahead of or on time. On recent coursework, Machine Learning at Scale, Gabriel took on the task to build machine learning model for the project, run various iterations of multiple algorithms leading to the final model of choice, including detailed hyper-parameter tuning. I would recommend him in any Data Scientist position and would love to collaborate again in future.
Credentials
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Natural Language Processing (NLP) Nanodegree
UdacityFeb, 2021- Oct, 2024 -
PMI Agile Certified Practitioner (PMI-ACP)
LinkedInJan, 2021- Oct, 2024 -
Feature Engineering for Machine Learning
UdemyJan, 2020- Oct, 2024 -
Learning Git and GitHub
LinkedInDec, 2019- Oct, 2024 -
NLP with Python for Machine Learning Essential Training
LinkedInDec, 2019- Oct, 2024 -
Python for Data Science and Machine Learning Bootcamp
UdemyDec, 2019- Oct, 2024 -
Block 1
HalliburtonJun, 2019- Oct, 2024 -
Basic Mud School
SchlumbergerJan, 2011- Oct, 2024 -
AWS Certified Machine Learning Engineer
Amazon Web Services (AWS)Oct, 2021- Oct, 2024 -
BOSIET
OPITONov, 2019- Oct, 2024 -
Microsoft Azure Certified Data Scientist
MicrosoftSep, 2021- Oct, 2024 -
Deepwater Certified Fluids Specialist
Schlumberger -
IWCF
International Well Control Forum -
PEC SAFELAND/SAFEGULF
PEC Safety
Experience
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Filos Technology
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United States
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Information Technology & Services
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1 - 100 Employee
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Machine Learning Engineer | Data Scientist
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May 2020 - Present
Collaborate with business partners and stakeholders to develop innovative solutions using Machine learning Algorithms. Driving strategy and vision for products by translating research, customer insights, and data discovery into innovative solutions for customers. Automate Machine Learning pipelines using SageMaker pipeline, Step function Lambda, and other AWS resources. Implement MLOps using SageMaker Projects Template. Catalog models for production, manage model version and automate model deployment. Built end-to-end Recommender Engine workflow using SageMaker pipeline. Created and registered model in AWS Model registry. Automated batch transform job. Developed post- processing lambda function that triggers events from S3 to DynamoDB. Scheduled cron job using SageMaker Model Monitor for model retraining. Took advantage of SageMaker PySpark integration to build a classification model using Random Forest algorithm. Serialize PySpark model to SageMaker model using MLeap. Performed batch transform job that predicted 5 % or more positive feedback from potential business targets resulting in a 6% increase in revenue. Built a predictive model that predicted energy consumption rates using SageMaker DeepAR (time-series) resulting in proactive plans on power adjustment and load estimation for quality customer service. Built Sentiments Analysis Model using Hugging face AWS Deep Learning transformer container. Run Hyperparameter tuning job and register the best model in AWS model registry. Collaborates closely with Agile team to refactor and test production code prior to deployment. Used multiple production variants for A/B testing with zero downtime Show less
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Halliburton
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United States
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Oil and Gas
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700 & Above Employee
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Data Scientist - Drilling Fluids | Halliburton
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Apr 2017 - May 2020
Conducted laboratory test experiments and performed Exploratory Data Analysis on drilling fluids samples collected downhole while drilling. Built a predictive model using lab results, sensor data, geological information, and drilling equipment variables to predict oil-well downhole pressure. Monitored real-time downhole drilling parameters window and readjusted accordingly to optimize drilling parameters. Performed pilot testing by building a model that simulate drilling parameters prior to drilling. Show less
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Schlumberger
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United States
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Oil and Gas
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700 & Above Employee
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Drilling Fluids Specialist
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Aug 2011 - Jun 2016
Delivered end of well recap technical presentations to stakeholders. Conducted laboratory testing and data analysis to determine chemical treatments required to optimize drilling parameters. Utilized sensor and laboratory data to build a well-pressure forecast model Simulated drilling parameters and built a predictive model that predicted Equivalent Circulating Density. Monitored real-time downhole drilling parameters for outliers detection and re-adjusted accordingly. Delivered end of well recap technical presentations to stakeholders. Conducted laboratory testing and data analysis to determine chemical treatments required to optimize drilling parameters. Utilized sensor and laboratory data to build a well-pressure forecast model Simulated drilling parameters and built a predictive model that predicted Equivalent Circulating Density. Monitored real-time downhole drilling parameters for outliers detection and re-adjusted accordingly.
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Education
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2020 - 2021
University of California, Berkeley
Master's degree, Data Science -
2016 - 2017
Texas A&M University
Drilling Engineering Program -
2002 - 2007
Rivers State University
Bachelor’s Degree, Petroleum Engineering
Community
