Data Scientist

Title: Data Scientist Location: Sacramento, CA Duration: 6 Month Contract to PERM Pay: $38-$40/hr Position Summary: 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. Must Haves: • Master’s degree or PhD in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field • 5+ years of hands-on experience building, validating, and deploying predictive models and machine learning solutions in production environments • Strong programming experience with Python or R, including ML libraries such as scikit-learn, XGBoost/LightGBM, and pandas • Advanced SQL skills with 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 • Proven ability to clearly communicate analytical findings to both technical and non-technical stakeholders • Experience working cross-functionally with data engineering and operational teams • Experience supporting data science initiatives within construction, manufacturing, or other asset‑intensive industries • Ability to manage multiple initiatives simultaneously and work independently Plusses: • Prior experience in construction, manufacturing, mining, energy, or other large-scale asset-intensive environments • Exposure to mobile equipment, heavy machinery, or industrial fleet operations • Hands-on experience with predictive maintenance, telematics, IoT sensors, or equipment management systems • Experience with time-series forecasting, reliability engineering, or survival analysis • Familiarity with MLOps practices, version control tools (GitHub, Azure DevOps), and Agile development • Experience with Power BI, Tableau, or similar data visualization tools Day to Day: • Design, develop, and deploy machine learning models supporting the mobile equipment group, focused on equipment health, reliability, and operational efficiency • Analyze structured and unstructured datasets including equipment telematics, maintenance, and operational data • Build proof-of-concept models with clearly defined success metrics and scale solutions into production pipelines • Collaborate closely with data engineering on data ingestion, feature engineering, and model deployment strategies • Translate model outputs into actionable decision-support insights for operational teams • Present analytical findings, model performance, and strategic recommendations to executive-level leadership and senior business stakeholders • Document model logic, assumptions, performance benchmarks, and data dependencies • Identify data quality gaps and recommend data enhancements to improve model accuracy and reliability • Contribute to broader data science and AI initiatives supporting construction operations