Data Scientist

Job Description Insight Global is searching for a highly skilled Data Scientist to support one of its largest oil & gas compression services clients in Houston, TX. This person will be responsible for building and optimizing advanced machine learning models focused on predictive maintenance, with a strong emphasis on time series data analysis. They will leverage Python/PySpark in environments such as Microsoft Azure/Fabric, Jupyter Notebooks, and VS Code to develop and refine models, while also working closely with business stakeholders to translate complex statistical concepts and model outputs into clear, actionable insights. The ideal candidate will have a deep understanding of machine learning and deep learning techniques, strong communication skills, and the ability to explain the "why" behind their work in a simplified way to non-technical audiences. This position will be based in Houston, TX and will follow a hybrid schedule of 3-4 days onsite. The pay rate for this position will be between $55-62/hr. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements Expert-level experience with time series analysis, including working with sequential/temporal data, identifying trends and seasonality, detecting anomalies, and building forecasting/predictive models (ARIMA, Prophet, LSTM, or similar) for real-world applications such as predictive maintenance Strong hands-on experience building and applying machine learning models across multiple techniques, with a solid foundation in statistics and data science principles Proven ability to translate complex data science concepts into clear, practical insights for business stakeholders, balancing both technical depth and business context Excellent communication skills, both verbal and written, with the ability to present findings clearly and confidently Proficiency in Python (and/or PySpark) for data analysis and model development Experience working in cloud environments such as Azure (preferred), AWS, or Databricks; familiarity with Microsoft Fabric is a plus Oil and Gas Experience