About the Company
Halliburton is one of the world’s largest providers of products and services to the global energy industry. The company focuses on innovation, technical expertise, and employee development, providing opportunities for professionals to grow their skills and careers while contributing to complex engineering and business challenges.
About the Role
Halliburton is seeking a Data Analyst – Entry Level for a remote role focused on data analysis, predictive modeling, data engineering, and machine learning. Working under general supervision, the successful candidate will analyze large and complex datasets, identify meaningful patterns, develop predictive models, and communicate findings through clear data visualizations. The role also involves collaborating with data engineers and applying cloud and distributed computing technologies to support reliable, repeatable analysis.
Key Responsibilities
Analyze large-scale business datasets, including time-series data and structured and unstructured information, from multiple sources to identify trends and actionable insights.
Perform data engineering, data modeling, and model deployment tasks under general supervision.
Use open-source machine learning and deep learning libraries to identify data patterns and develop predictive models.
Conduct statistical analyses to evaluate trends and determine significant relationships within datasets.
Collaborate with data engineers to design and build data pipelines that support reproducible analysis.
Apply cloud computing technologies, including Microsoft Azure, and distributed computing tools such as Apache Spark.
Work with large datasets, including terabyte-scale data, to uncover patterns and support business analysis.
Prepare and present analytical findings using graphs, charts, tables, and other data visualization methods.
Stay informed about developments in machine learning and artificial intelligence and assess relevant techniques for analytical work.
Contribute to collaborative engineering projects through effective communication and teamwork.
Required Qualifications An undergraduate degree in a STEM field.
Industry experience in predictive modeling, data science, and data analysis.
Knowledge of machine learning frameworks and packages, including Keras, TensorFlow, and Scikit-learn.
Experience with cloud computing platforms such as Microsoft Azure.
Programming experience in Python, R, and Scala.
Experience working with distributed computing technologies such as Apache Spark.
Experience handling large datasets and using data analysis and visualization tools.
Strong communication and teamwork skills, with the ability to collaborate on complex engineering projects.
Preferred Qualifications A master’s degree in a STEM field is preferred.
Additional Considerations
Candidates whose qualifications exceed the minimum requirements may be considered for higher-level roles, depending on their experience, additional role requirements, and business needs.