Jobs via Dice
Senior Machine Learning Scientist/AI/ML Engineer Power & Renewables
Jobs via Dice, Juno Beach, Florida, United States
Overview
We are seeking a highly skilled
Data Scientist
with deep expertise in
machine learning, quantitative modeling, and energy markets . This role focuses on developing intelligent forecasting, optimization, and autonomous decision systems to support power trading and market analytics. Key Responsibilities
Design and implement advanced machine learning and AI models for power market forecasting, optimization, and trading insights. Build and deploy production-grade analytics pipelines in cloud environments (AWS, Azure, or Google Cloud Platform). Develop LLM- and agent-based frameworks for autonomous market monitoring, data analysis, and decision support. Perform time-series forecasting for price, load, and renewable generation using models such as ARIMA, Prophet, LSTM, and XGBoost. Conduct quantitative modeling, including optimization, stochastic simulation, and risk analysis (Monte Carlo, VaR). Create and maintain data architectures and pipelines (ETL/ELT, dbt, Airflow, Prefect) with strong governance and versioning practices. Deliver actionable insights through visual analytics and dashboards (Power BI, Tableau, Plotly) for traders and leadership. Translate technical findings into clear, concise business narratives. Core Qualifications
Master s or Ph.D. in Data Science, Computer Science, Engineering, Finance, or Applied Mathematics. 5+ years in data science or machine learning (with 2+ years in energy/power markets). Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch, TensorFlow) and SQL. Expertise in statistics, linear algebra, and optimization. Experience deploying scalable ML models in AWS, Azure, or Google Cloud Platform environments. Preferred Expertise
Hands-on with LLMs (GPT, Llama, Mistral) and RAG pipelines for report generation and market insights. Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI). Experience integrating weather, grid, and market data for predictive analytics. Proficiency with vector databases (FAISS, Pinecone, Weaviate) and data warehouses (Databricks, Snowflake). Strong communication and documentation discipline; thrives in high-stakes, time-sensitive environments Bonus Qualifications (Energy Domain)
Knowledge of ISO/RTO markets (PJM, ERCOT, MISO, CAISO). Understanding of power trading instruments (DA/RT markets, FTRs, CRRs, PPAs, futures, swaps). Familiarity with natural gas, renewables, and carbon markets. Experience modeling LMPs, congestion, and portfolio risk. Awareness of regulatory data (FERC, EIA, ISO). Seniority level
Mid-Senior level Employment type
Full-time Job function
Other Industries
Software Development
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We are seeking a highly skilled
Data Scientist
with deep expertise in
machine learning, quantitative modeling, and energy markets . This role focuses on developing intelligent forecasting, optimization, and autonomous decision systems to support power trading and market analytics. Key Responsibilities
Design and implement advanced machine learning and AI models for power market forecasting, optimization, and trading insights. Build and deploy production-grade analytics pipelines in cloud environments (AWS, Azure, or Google Cloud Platform). Develop LLM- and agent-based frameworks for autonomous market monitoring, data analysis, and decision support. Perform time-series forecasting for price, load, and renewable generation using models such as ARIMA, Prophet, LSTM, and XGBoost. Conduct quantitative modeling, including optimization, stochastic simulation, and risk analysis (Monte Carlo, VaR). Create and maintain data architectures and pipelines (ETL/ELT, dbt, Airflow, Prefect) with strong governance and versioning practices. Deliver actionable insights through visual analytics and dashboards (Power BI, Tableau, Plotly) for traders and leadership. Translate technical findings into clear, concise business narratives. Core Qualifications
Master s or Ph.D. in Data Science, Computer Science, Engineering, Finance, or Applied Mathematics. 5+ years in data science or machine learning (with 2+ years in energy/power markets). Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch, TensorFlow) and SQL. Expertise in statistics, linear algebra, and optimization. Experience deploying scalable ML models in AWS, Azure, or Google Cloud Platform environments. Preferred Expertise
Hands-on with LLMs (GPT, Llama, Mistral) and RAG pipelines for report generation and market insights. Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI). Experience integrating weather, grid, and market data for predictive analytics. Proficiency with vector databases (FAISS, Pinecone, Weaviate) and data warehouses (Databricks, Snowflake). Strong communication and documentation discipline; thrives in high-stakes, time-sensitive environments Bonus Qualifications (Energy Domain)
Knowledge of ISO/RTO markets (PJM, ERCOT, MISO, CAISO). Understanding of power trading instruments (DA/RT markets, FTRs, CRRs, PPAs, futures, swaps). Familiarity with natural gas, renewables, and carbon markets. Experience modeling LMPs, congestion, and portfolio risk. Awareness of regulatory data (FERC, EIA, ISO). Seniority level
Mid-Senior level Employment type
Full-time Job function
Other Industries
Software Development
#J-18808-Ljbffr