Job Description Insight Global is seeking a Data Scientist to support the Mobile Equipment group within a large, asset intensive construction organization. This role focuses on designing, developing, and deploying data science and machine learning solutions that improve mobile equipment operations, including predictive maintenance, fleet performance, equipment reliability, and downtime reduction. This individual will work cross functionally with data engineering, operations, and business leaders to translate complex equipment and operational data into scalable, production ready analytics, while regularly presenting insights to executive-level leadership." 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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Skills and Requirements Must Have:

•  Prior experience in construction, manufacturing, mining, energy, or other large-scale asset-intensive environments
•  5+ years o hands on experience building, validating, and deploying predictive models and machine learning solutions in production environments
•  Programming experience w/ Python or R, including ML libraries such as scikit-learn, XGBoost/LightGBM, and pandas
•  Experience supporting Data Science initiatives within construction, manufacturing, energy, or transportation
•  SQL experience working in cloud-based data platforms (Azure, Databricks, or similar)
•  Strong understanding of feature engineering, model validation, evaluation metrics, and mitigation of data leakage
•  Strong presentation and communication experience (analytics findings to technical and non-technical stakeholders)
•  Experience working cross-functionally with data engineering and operational teams