Top Energy Data & Analytics Jobs in New York City, NY

As a Mid-level Applied AI Data Scientist, you will apply statistical methods and machine learning to derive business insights from data and create Tableau visualizations.

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

The PLEXOS Modeling Consultant develops and evaluates models using PLEXOS software, collaborates with teams on modeling strategies, translates data into visual formats, and communicates findings to clients, promoting solutions to energy-related issues.

The Senior Associate, Portfolio Compliance ensures compliance with client guidelines and regulatory requirements, manages compliance alerts, and collaborates with multiple teams for reporting and certification.

The role involves developing quantitative models for trading strategy and asset optimization, mentoring junior analysts, and collaborating across teams to enhance analytical capabilities.

The Senior Client Data & Analytics Lead guides clients in developing data capabilities, coaching their teams, and translating needs for product delivery. This role combines data leadership with client interaction and strategic planning.

Lead energy analytics, market intelligence, AI integration, and collaborate with teams to optimize performance and growth in energy solutions.

As an Analyst, you'll execute VPP and demand response programs, optimize asset performance, and develop market strategies in energy storage.

The Sr System Analyst, Data Activation Engineer designs and builds data integration pipelines, ensuring data integrity and validating data contracts for analytics platforms. This collaborative role requires functional and technical interface design, monitoring pipelines, and documenting processes to deliver reliable data.

The Quantitative Researcher for Monetization will develop strategies for market opportunities, optimize performance using data, and apply machine learning in financial energy systems.