Trace Smith Email & Phone Number

Houston, TX, US

Houston, TX, US

Seattle, WA, US

Helping energy customers solve complex problems on AWS.- GenAI- ML & Optimization - Data Platform- Networking/Security

Seattle, WA, US

• Architected and developed a virtual smart assistant using Amazon Bedrock Agents and LLMs to optimize well planning workflows and accelerating engineers retrieving drilling operations reports/summaries/kpis.
• Architected and deployed a real-time drilling advisory system consisting of ETL data pipelines, database management, batch processing, and web application deployment.
• Lead data platform developer responsible for implementing a large scale enterprise data platform using a data mesh architecture on AWS. Developed IaC and automation tooling for core platform component; developed.
• Developed a large-scale Predictive Maintenance application to mitigate equipment wear, failures, and unplanned downtime. Deployed real-time anomaly detection pipeline for asset health monitoring; closed loop solution.
• Developed a scalable, end-to-end, machine learning application to support training thousands of pricing optimization and forecasting time series models. Tech Stack: AWS Batch and SageMaker Pipelines.

US

• Responsible for designing and productionizing a scalable end-to-end Machine Learning pipeline Azure for high impacting global pricing optimization models (ExxonMobil Chemical Company).
• Developed time-series classification model to predict attrition for thousands of customers. Crafted hundreds of lagged features from millions of historical transactions on thousands of customers and key economic.
• Implemented infrastructure as code to automate provisioning multiple environments for virtual machines, networking, container registry, and Azure Kubernetes Services (AKS).
• Created anomaly detection algorithm for continuous well surveillance monitoring for thousands of oil and gas assets and dynamically routing operators to wells indicating mechanical equipment failures.
• Developed a deep-learning time series classification model for predicting downhole drilling non-productive events. Trained models offline, deployed models with REST endpoint, performed real-time inference using Spark.
• Constructed a custom Python algorithm in conjunction with Azure Cognitive Services OCR engine to extract unstructured tables across thousands of scanned PDF documents in order to obtain competitive insights into.

Mountain View, California, US

• Perform code reviews and evaluations of machine learning projects submitted by Udacity students and provide students with Data Science Career consulting and advice; strive to give actionable and helpful feedback to the.

Houston, Texas, US

• Research: Geostatistical analysis of microseismic data in fracture modelling; patent pending: https://patents.google.com/patent/GB2569900A/en
• Created model using Factor Analysis (FA), a data reduction technique, and Classification and Regression Trees (CART), a predictive data mining technique for predicting oil and gas production of a prospective well; both.

Houston, Texas, US

• Research: ‘Pseudo Phase Production Simulation’ – Developed a method to assess multiphase flow production via relative permeability in reservoir flow simulations in order to rank Petrophysical realizations.

Master Of Science (Ms), Data Science

Master Of Science (Ms), Petroleum Engineering

Bachelor Of Science (Bs), Petroleum Engineering