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Data Scientist
2 meses atrás
Responsibilities :
Utilize your expertise in unsupervised and supervised learning techniques, particularly in the context of predictive maintenance, to analyze large volumes of data and develop models for capturing and predicting the life and condition of hydraulic fracturing equipment.
Leverage your experience with big data analysis using Spark to develop efficient and scalable solution strategies. Prepare consolidated datasets for modeling, deploy models, and create BI reports presenting findings and recommended actions.
Effectively communicate with business leaders and field personnel, providing a clear understanding of the merits and limitations of data-driven solutions. Articulate data-driven inferences to set realistic expectations that drive the creation of improved business processes supported by data.
Demonstrate maturity in big data analytics by delivering solutions within defined time and budgetary constraints.
Apply statistical inference and other statistical tools to extract meaningful insights from data, supporting informed decision-making across the organization.
Perform other job-related duties or special projects as assigned, contributing to the continuous improvement and innovation within the data science domain. Knowledge, Skills, and Abilities Requirements :
Undergraduate degree in any STEM related field; Masters or PhD preferred. Experience with unsupervised and supervised learning techniques preferably in the context of predictive maintenance; preference will be given to candidates with prior experience with modeling the life and condition of equipment’s, components or subjects.
Experience with analysis of big data using Spark.
Experience working with cloud platforms for big data analytics such as Databricks or Snowflake and with major cloud providers such as Azure or AWS.
Expert proficiency in SQL and Python.
Expert proficiency in visualization and BI tools such as PowerBI, Tableau, Plotly.
Expert proficiency with statistical inference and other statistical tools to extract and communicate insights from data.
Familiarity with common Machine Learning techniques for regression and classification.
Desirable:
Oil and gas industry experience preferred.
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Location São Paulo, SP - Brazil
Job Details Requisition Number: 189939
Experience Level: Experienced Hire Job Family: Engineering/Science/Technology Product Service Line: Production Enhancement
Full Time / Part Time: Full Time Additional Locations for this position:
São Paulo, SP - Brazil
