Data Scientist

ManpowerGroup Global, Inc.

Norge, Lehi (OK, UT)

On-site

USD 100,000 - 130,000

Full time

14 days+

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Job summary

A leading energy solutions provider in the United States is seeking a Staff Data Scientist to enhance home energy intelligence through advanced data models. This role involves developing predictive models for energy efficiency and demand-response strategies while collaborating with technical teams. The ideal candidate will have over 5 years in the energy sector, strong skills in Python and predictive modeling, and the capability to communicate complex insights effectively. This position is onsite in Lehi, UT, offering a 12-month contract.

Qualifications

  • 5+ years of energy industry experience with technical leadership in modeling initiatives.
  • Proficiency in energy forecasting or Demand Response optimization.
  • Expertise in predictive modeling and applied ML techniques.

Responsibilities

  • Build and deploy advanced predictive models for occupancy and cost forecasting.
  • Optimize energy operations using data-driven insights.
  • Transform legacy data into robust, reusable data products.

Skills

Predictive modeling
Energy forecasting
Statistical analysis
Python
Communication skills

Education

Advanced degree (MS/PhD) in a quantitative field

Tools

Pandas
NumPy
scikit-learn
PySpark
Spark
Databricks
GCP

Job description

Data Scientist

  • 12 month contract
  • Onsite M-Th in Lehi, UT
  • W2 only
SUMMARY

The company is redefining home energy intelligence through data and AI to enable personalized comfort, energy efficiency, and demand-response optimization across millions of connected homes. We are seeking a Staff Data Scientist to design and deploy predictive models that enable intelligent home energy decisions: from forecasting comfort and cost to optimizing EV charging and demand response events.

DUTIES
  • Develop Predictive Models: Build and deploy advanced models for occupancy, runtime, cost forecasting, anomaly detection, and preconditioning to enable comfort-aware, energy-efficient control and maintenance.
  • Optimize Energy Operations: Use data-driven insights to improve the reliability and precision of Demand Response (DR), Time-of-Use (TOU) shifting, and Virtual Power Plant (VPP) strategies.
  • Advance Data Quality & Scalability: Partner with data engineering to transform legacy data structures into robust, documented, and reusable data products that support ML and real-time analytics.
  • Cross-Functional Collaboration: Work closely with product, engineering, and analytics teams to embed intelligence into production systems and shape future data-driven energy experiences.
  • Communicate Impact: Translate complex model outcomes into actionable insights for both technical and non-technical audiences.
REQUIREMENTS
  • 5+ years of energy industry experience, including demonstrated technical leadership on high-impact modeling initiatives.
  • Experience with energy forecasting, thermal modeling, or Demand Response optimization.
  • Understanding energy markets, Distributed Energy Resources (DER), and Virtual Power Plant (VPP) concepts.
  • Proven expertise in predictive modeling, forecasting, and applied ML (e.g., regression, gradient boosting, time-series, causal inference).
  • Experience working with large-scale event and sensor data, preferably within energy, IoT, or device-driven ecosystems.
  • Strong proficiency in Python (Pandas, NumPy, scikit-learn, PySpark) and experience with distributed compute environments (Spark, Databricks, GCP).
  • Ability to take models from concept to production in collaboration with engineering partners.
  • Skilled in statistical analysis, feature engineering, and experimental design (e.g., A/B testing).
  • Excellent communication and storytelling skills for complex, data-driven topics.
PREFERRED QUALIFICATIONS
  • Familiarity with LLM or generative AI applications in analytics and optimization.
  • Advanced degree (MS/PhD) in a quantitative field such as Statistics, Computer Science, or Engineering.

If this is a role that interests you and you’d like to learn more, click apply now and a recruiter will be in touch with you to discuss this great opportunity. We look forward to speaking with you!

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