Staff Data Scientist

Insight Global; Lehi (UT); On-site; USD 89,544 - 103,320; Part time

Job summary

A leading staffing company is seeking a Staff Data Scientist to design and deploy predictive models focusing on home energy decisions. The role involves enhancing energy strategies and collaborating with cross-functional teams, requiring 5-8 years of relevant experience and strong skills in predictive modeling, Python, and large-scale data processing. The position is contract-based with a pay range of $65-$75/hr.

Qualifications

• 5-8 years of experience in predictive modeling and applied machine learning.
• Experience in energy, IoT, or device-driven ecosystems is preferred.
• Strong mathematical and analytical skills.

Responsibilities

• Design and deploy advanced models for energy efficiency.
• Enhance accuracy of Demand Response and energy strategies.
• Collaborate with engineering and analytics teams.

Skills

Predictive modeling

Applied machine learning techniques

Python proficiency

Experience with large-scale event and sensor data

Tools

Python (Pandas, NumPy, scikit-learn, PySpark)

Distributed computing environments (Spark, Databricks)

Job description

This range is provided by Insight Global. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$65.00/hr - $75.00/hr

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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
• 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

Seniority level

Mid‑Senior level

Employment type

Contract

Job function

Other

Industry: Software Development

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