Insight Global
Staff Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Staff Data Scientist with a 6-month contract, offering $65-75/hr. Required skills include predictive modeling, Python, and experience in energy forecasting. An advanced degree and 7+ years in energy or IoT ecosystems are essential.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
600
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🗓️ - Date
November 21, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Lehi, UT
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🧠 - Skills detailed
#Data Engineering #Generative Models #Python #GCP (Google Cloud Platform) #Anomaly Detection #Distributed Computing #Pandas #Regression #Leadership #Databricks #Forecasting #Spark (Apache Spark) #IoT (Internet of Things) #AI (Artificial Intelligence) #PySpark #ML (Machine Learning) #NumPy #Data Science #Predictive Modeling
Role description
About the Company
Insight Global is a leading staffing and services company that connects top talent with innovative organizations. Our mission is to empower people and businesses to achieve their goals through exceptional service and expertise.
About the Role
One of Insight Global's clients is looking for a Staff Data Scientist to join their team. This individual will design and deploy predictive models that enable intelligent home energy decisions.
Responsibilities
• Design and deploy advanced models for occupancy, runtime, cost forecasting, anomaly detection, and preconditioning to enable comfort-aware, energy-efficient control and maintenance.
• Leverage data-driven insights to enhance the accuracy and reliability of Demand Response (DR), Time-of-Use (TOU) shifting, and Virtual Power Plant (VPP) strategies.
• Collaborate with data engineering to modernize legacy structures into robust, documented, and reusable data products that support machine learning and real-time analytics.
• Partner with product, engineering, and analytics teams to embed intelligence into production systems and shape future data-driven energy experiences.
• Translate complex model outputs into clear, actionable recommendations for both technical and non-technical stakeholders.
Qualifications
• 5-8 Years of experience
• Proven expertise in predictive modeling, forecasting, and applied machine learning techniques (e.g., regression, gradient boosting, time-series analysis, causal inference).
• Hands-on experience working with large-scale event and sensor data, ideally within energy, IoT, or device-driven ecosystems.
• Strong proficiency in Python (including Pandas, NumPy, scikit-learn, PySpark)
• Experience with distributed computing environments such as Spark, Databricks, or GCP.
Required Skills
• Expertise in energy forecasting, thermal/comfort modeling, or Demand Response optimization
• Deep understanding of energy markets, DER, and Virtual Power Plant (VPP) concepts
• Experience applying LLM or generative AI in analytics and optimization
• Advanced degree (MS/PhD) in a quantitative field
• 7+ years of industry experience with proven technical leadership on high-impact modeling initiatives
Preferred Skills
• Experience with advanced AI applications such as generative models and energy forecasting to push the boundaries of predictive analytics within the energy domain.
Pay range and compensation package
65-75/hr
About the Company
Insight Global is a leading staffing and services company that connects top talent with innovative organizations. Our mission is to empower people and businesses to achieve their goals through exceptional service and expertise.
About the Role
One of Insight Global's clients is looking for a Staff Data Scientist to join their team. This individual will design and deploy predictive models that enable intelligent home energy decisions.
Responsibilities
• Design and deploy advanced models for occupancy, runtime, cost forecasting, anomaly detection, and preconditioning to enable comfort-aware, energy-efficient control and maintenance.
• Leverage data-driven insights to enhance the accuracy and reliability of Demand Response (DR), Time-of-Use (TOU) shifting, and Virtual Power Plant (VPP) strategies.
• Collaborate with data engineering to modernize legacy structures into robust, documented, and reusable data products that support machine learning and real-time analytics.
• Partner with product, engineering, and analytics teams to embed intelligence into production systems and shape future data-driven energy experiences.
• Translate complex model outputs into clear, actionable recommendations for both technical and non-technical stakeholders.
Qualifications
• 5-8 Years of experience
• Proven expertise in predictive modeling, forecasting, and applied machine learning techniques (e.g., regression, gradient boosting, time-series analysis, causal inference).
• Hands-on experience working with large-scale event and sensor data, ideally within energy, IoT, or device-driven ecosystems.
• Strong proficiency in Python (including Pandas, NumPy, scikit-learn, PySpark)
• Experience with distributed computing environments such as Spark, Databricks, or GCP.
Required Skills
• Expertise in energy forecasting, thermal/comfort modeling, or Demand Response optimization
• Deep understanding of energy markets, DER, and Virtual Power Plant (VPP) concepts
• Experience applying LLM or generative AI in analytics and optimization
• Advanced degree (MS/PhD) in a quantitative field
• 7+ years of industry experience with proven technical leadership on high-impact modeling initiatives
Preferred Skills
• Experience with advanced AI applications such as generative models and energy forecasting to push the boundaries of predictive analytics within the energy domain.
Pay range and compensation package
65-75/hr
