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Weatherford’s Production business is seeking a Data Scientist who is passionate about data and wants to apply machine learning techniques to solve problems for our customers. This person is expected to be proficient in the exploration and understanding of structured and unstructured data, machine learning techniques, statistical modeling methods, predictive analytics, anomaly detection, and supervised and unsupervised learning. The successful candidate will work with stakeholders to leverage data to solve critical business problems in the oil & gas production domain.
The Data Scientist will work on all aspects of the design, development and delivery of machine learning enabled solutions including problem definition, data acquisition, data exploration, feature engineering, experimenting with various ML algorithms, evaluating metrics, deploying models and iteratively improving the total solution. He or she will work with data from diverse, unstructured formats including numerical, time series, text, and image.
- Formulate meaningful hypothesis that are relevant to the business objectives.
- Design and train models for use in production environments.
- Mine structured and unstructured data for patterns.
- Utilize data from databases, historians, and/or data lakes.
- Rigorously build, analyze and compare machine learning or statistical models; there is a strong emphasis on programming using the most popular machine learning languages such as Python.
- Work with application developers to develop data-analytics products that are deployed to end-users as part of packaged solutions.
- Visualize and report findings of deployed data analytics solutions to provide insights to the organization and our customers.
- B.S. or higher in Engineering, Mathematics, Statistics or Computer Science with significant experience in data analytics.
- MS degree with 5+ years experience is preferred.
- Expertise in predictive modeling, machine learning and statistics.
- Software development skills in one or more high level languages (Python/Java/R/Scala).
- Experience using one or more of the following common ML software packages: scikit-learn, TensorFlow, NumPy, pandas, jupyter.
- Well-versed in machine learning algorithms and their suitability for solving various problems: Regression, Bayesian, Support Vector Machines, Decision Trees, Random Forest, Clustering, Neural Networks.
- Experience in using SQL/No SQL databases is an advantage
- Experience working in Linux is an advantage
- Experience with Big Data technologies is an advantage (Hadoop, Hive, Spark, Cassandra).
- Good critical thinking, technical, data collection and user interviewing skills.
- Ability to work as a team member in a fast-paced environment.
- Experience with Agile software development processes is preferred.
- Experience with Cloud service offerings from AWS, Azure or GCP is a plus.