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The primary responsibility of the E&P IT Specialist Data Science, Analytics is the technical implementation of an enterprise class machine learning environment. The successful candidate will be responsible for constructing high quality computer based probabilistic models to answer business problems, providing technical recommendations in support of an machine learning roadmap, developing the infrastructure necessary to interact with models and establish sustainable methods for deployment and support of the models.
The Analytics Specialist Data Science position is a business facing role, accountable for the end-to-end usage and value creation for analytics models and workflows. The ideal candidate will have a computer science degree or equivalent, 5-10 years experience, a high level of mathematical and statistical knowledge, a deep understanding of the business function and industry best practices; and the ability to recognize data patterns and relate them to real world scenarios.
The successful candidate will work closely with an Asset, Functional Excellence, and IT teams on a variety of projects from framing through deployment and ongoing continuous improvement efforts. Work will include strategic reviews, profiling and scoring opportunities, data identification and cleansing, problem solving, process reengineering and business engagement.
Strong people and communication skills, and sound analytical and interpersonal skills are essential for success in this position. A strong sense of ownership and a drive to improve existing systems and processes is needed.
ROLE / RESPONSIBILITIES:
Interpret key business problems and hypothesize/targets for improvement into actionable machine learning task
Build and deploy Machine Learning infrastructure
o High performing Machine Learning models
o Provide statistical verification of model quality
o Easily accessible middleware layers for interactions with models
o Maintain versioning and documentation of model builds for backwards
capability and audit purposes
o Organize and monitor support of models in production
Analyze and apply the results of the model to the business problem
Conduct opportunity reviews to evaluate readiness, value, and delivery capabilities
Understand business process work flows and applicability to models
Develop ETL and Data Repository solutions to support machine ,earning and analytics projects
Strong understanding of cloud offerings specifically Azure
o Azure SQL
o Azure DW
o Azure Blob
o Azure Data Factory
High level mathematical and statistical abilities
Familiarity with domain data and quality
Innovator and Value Creator
Good Problem solving techniques; critical and logical thinking
Good communication skills; Ability to work with all levels of the organization and high level of interpersonal skills in managing team members and customer relationships
Solid understanding of data concepts such as master data, data governance, and integration based on key fields, etc.
High performance delivery focus with an emphasis on task ownership and completion. Self-motivated with an enthusiastic, methodical and diligent approach
Ability to multi-task and be flexible
Knowledge of oil & gas well lifecycle or at least significant areas, e.g. production engineering, operations, D&C, in conventional and unconventional assets. This includes understanding current business practices / processes, key technical and business challenges, and knowledge of workflows to other parts of the business.
Lean training a plus
EXPERIENCE / QUALIFICATIONS:
Bachelors Degree in Statistics, Engineering, Computer Science, or equivalent
5-10 years significant and relevant E&P engineering experience
Proven experience with relationship management
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