Lead, Energy Systems Data Science

Location: San Francisco, CA, US, Chicago, IL, US

Employment Type: OTHER

Overview

Company Overview

 

Pattern Energy is a leading renewable energy company that develops, constructs, owns, and operates high-quality wind and solar generation, transmission, and energy storage facilities. Our mission is to transition the world to renewable energy through the sustainable development and responsible operation of facilities with respect for the environment, communities, and cultures where we have a presence. 

 

Our approach begins and ends with establishing trust, accountability, and transparency. Our company values of creative spirit, pride of ownership, follow-through, and a team-first attitude drive us to pursue our mission every day. Our culture supports our values by fostering innovative and critical thinking and a deep belief in living up to our promises.

 

Headquartered in the United States, Pattern has a global portfolio of more than 30 power facilities and transmission assets, serving various customers that provide low-cost clean energy to millions of consumers.

Responsibilities

Job Purpose

 

The Lead, Energy Systems Data Science will own the creation, validation, and continuous improvement of model-ready datasets for Pattern’s internal capacity expansion and production cost modeling suite (WIS:dom). This position sits at the intersection of energy markets, data science, and strategic decision-making, helping shape how Pattern evaluates opportunities across North America. The role ensures that WIS:dom inputs and outputs are traceable,

credible, reproducible, and fit for use in asset valuation, market forecasting, development decision making, and portfolio strategy. The role serves as a key connector across Model Development, Market Strategy, Meteorology, Grid Integration, Data Engineering, and other subject matter expert teams, helping translate diverse expertise into a unified analytical framework. The successful candidate will help bridge technical domains, ensuring that complex analyses are grounded in both rigorous data science and real-world business needs.

 

Key Accountabilities

• Lead the creation and maintenance of model-ready data inputs and core output tables for WIS:dom modelling. Work with the Model Development team on requirements, balancing flexibility, accuracy and speed to insight. Highlight key assumptions and assist modelers in the interpretation of model input to result.
• Advance WIS:dom’s core datasets and analytical methods. Identify new sources and techniques, lead data discovery for new models and markets, and evaluate whether new information materially improves forecast quality or business insight.
• Lead the validation and continuous improvement of model inputs and outputs. Build automated quality checks, benchmarking scripts, diagnostic analyses, and visualizations; partner with subject-matter experts to confirm fitness for use and investigate why model results change.
• Develop decision-support visualizations and curated data products in Power BI, GIS, and related tools; partner with Data Engineering/Ops and enterprise technology teams to deliver reliable outputs to front-end systems.

Qualifications

Expereince/Qualifications/Education Required

Education Required

• Bachelor's degree in Meteorology, Engineering, Data Science, or a related quantitative field.

Experience Required

• 5+ years of experience in energy analytics, power markets modelling, utility planning, forecasting, or related quantitative work, or graduate study equivalent.
• Deep understanding of fundamental power systems datasets, including weather, load, generation, transmission, fuel, emissions, geospatial, technoeconomic, and market price data.
• Demonstrated ability to manage complex data models while preserving lineage, assumptions, limitations, and reproducibility.
• Experience leading data discovery and validation efforts with subject-matter experts and resolving conflicting or incomplete source information.

Qualifications

• Strong written and verbal communication skills, including the ability to explain technical limitations and findings to non-technical and senior stakeholders.
• Ability to collaborate effectively and seek input within and across teams.

Technical Skills

• Excellent programming skills, including building data transformation and validation routines.
• Experience applying software development best practices, including version control tools such as Git.
• Experience developing decision-ready visualizations using Power BI, GIS, or comparable visualization tools.
• Familiarity with high-performance remote server computing environments (Linux). (Preferred)
• Familiarity with cloud data platforms such as Azure, Databricks, or similar technologies. (Preferred)
• Experience handling and processing large datasets using parallel processing techniques and other performance optimization methods. (Preferred)

Additional Requirements

• Ability to maintain data quality, traceability, and reproducibility across complex analytical workflows.
• Ability to influence and gain alignment from cross-functional stakeholders when working through data quality or source discrepancies.
• Strong analytical, problem-solving, and critical-thinking skills.
• Ability to work effectively in a fast-paced, collaborative environment.

The expected starting pay range for this role is $111,000 - $138,000 USD. This range is an estimate and base pay may be above or below the ranges based on several factors including but not limited to location, work experience, certifications, and education. In addition to base pay, Pattern’s compensation program includes a bonus structure for full-time employees of all levels. We also provide a comprehensive benefits package which includes medical, dental, vision, short and long-term disability, life insurance, voluntary benefits, family care benefits, employee assistance program, paid time off and bonding leave, paid holidays, 401(k)/RRSP retirement savings plan with employer contribution, and employee referral bonuses.

 

Pattern Energy Group is an Equal Opportunity Employer.

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