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Role Summary:Â
This role will support and drive growth within the Advanced Analytics team, which is focused on using quantitative models to support business decisions. This is an exciting role to participate in a developing department and to shape how Advanced Analytics is used to support safety, operations, and financial goals in multiple lines of business.Â
 Responsibilities & Essential Functions include:Â
Partner with Subject Matter Experts in various lines of business to identify opportunities to apply quantitative methods, automated solutions, and analytical frameworks to improve business performance and process efficienciesÂ
Use foundational data science methodologies and input from Subject Matter Experts to identify relationships/drivers in data assets to improve key metrics of safety, predictive failure detection, asset performance, and financial forecastingÂ
Build, test, document, and deploy ML (machine learning), DP (deep learning), AI (artificial intelligence), models to produce value from data assetsÂ
Maintain a sustainable environment to validate that the models continue to work effectively and with up-to-date model documentationÂ
Prepare visualizations, and example output to demonstrate and explain model behavior, performance, and limitations to non-analytical team members and Subject Matter ExpertsÂ
Organize datasets for analysis from a variety of formats such as databases, technical and natural text documents, spreadsheets, time history, and imagesÂ
Normalize, and prepare data as necessary prior to exploration, visualization, analysis, modeling, and predictionÂ
And other duties as assigned.Â
 Position Requirements:Â
5+ years of experience in analytical data modeling of equipment reliability, finance, or econometrics.Â
5+ years of experience with various databases, data historians, and data query tools, such as OSISoft, ESRI, MSSQL, Oracle, MySQL, etc.Â
Master’s Degree in Data Science, Statistics, Econometrics, Mathematics, Engineering, Finance, Physics, or related discipline is preferred. A Bachelor’s degree is required.Â
Experience with DevOps, Python, Azure ML, Databricks, MS Fabric or other machine learning and/or statistical softwareÂ
Ability to clearly convey modeling results to a wide range of audiencesÂ
5+ years of experience in the midstream oil & gas industry is preferred.Â
 Travel Requirements: Â
Ability to travel up to 25% domestically and internationallyÂ
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