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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!

About ManpowerGroup, Parent Company of: Manpower, Experis, Talent Solutions, and Jefferson Wells

ManpowerGroup® (NYSE: MAN), the leading global workforce solutions company, helps organizations transform in a fast-changing world of work by sourcing, assessing, developing, and managing the talent that enables them to win. We develop innovative solutions for hundreds of thousands of organizations every year, providing them with skilled talent while finding meaningful, sustainable employment for millions of people across a wide range of industries and skills. Our expert family of brands - Manpower, Experis, Talent Solutions, and Jefferson Wells - creates substantial value for candidates and clients across more than 75 countries and territories and has done so for over 70 years. We are recognized consistently for our diversity - as a best place to work for Women, Inclusion, Equality and Disability and in 2022 ManpowerGroup was named one of the World's Most Ethical Companies for the 13th year - all confirming our position as the brand of choice for in-demand talent.