Data Scientist
On-siteDetroit, Michigan, United States
Job Summary
Design and maintain scalable ETL pipelines to process advanced metering infrastructure, utility bills, and building metadata with high consistency. Develop machine learning models for forecasting energy usage, detecting anomalies, and optimizing building performance at asset and portfolio levels. Benchmark building performance using interval data to support compliance with ESG frameworks such as NABERS and GRESB. Stabilize the EnerG data architecture within KODE OS and collaborate cross-functionally to deliver intelligent building features. Leverage large-scale building data to uncover usage patterns and regional trends that inform product strategy. Requires 5+ years in data science or energy systems with Python, SQL, and cloud platform proficiency. Competitive salary, discretionary bonus, and comprehensive health insurance.
Required Qualifications
- 5+ years of experience in data engineering, analytics, or applied data science, with a strong background in energy systems, sustainability, or ESG reporting
- Proven track record of designing and implementing scalable ETL pipelines with an emphasis on data quality, consistency, and operational performance
- Hands-on experience with energy-related datasets, including advanced metering data, utility bills, and building metadata
- Strong understanding of ESG frameworks and sustainability metrics such as NABERS, GRESB, and ENERGY STAR
- Proficiency in Python, SQL, and experience working with cloud-based data platforms (e.g., AWS, GCP, or Azure)
- Experience building ML/AI models for forecasting, optimization, and anomaly detection in the context of energy or building data
- Self-starter mindset with the ability to work independently, identify challenges proactively, and deliver end-to-end solutions
Desired Qualifications
- Passion for sustainability, energy efficiency, and building data-driven products that support climate and ESG goals
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