Data Scientist

No 3rd Parties

No Visa Candidates

Onsite: Juno Beach, FL

Data Scientist

• Data Science & Analytics & Machine Learning for Power Commodity Trading
• Focus is on the Data Science within the Energy, Power or Commodities Markets

Core Qualifications

• Master’s in Data Science, Computer Science, Finance, Engineering, or Applied Mathematics
• 5+ years of experience in machine learning or advanced analytics, with at least 2 years in energy, power, or commodities markets
• Proficiency in Python (pandas, NumPy, scikit-learn, PyTorch, TensorFlow) and SQL
• Experience deploying production-grade ML and analytics systems in AWS, Azure, or GCP
• Strong foundation in statistics, linear algebra, and optimization

Domain Expertise – Power & Commodities:

• Understanding of power market dynamics (generation, transmission, demand forecasting, ISO/RTO markets such as PJM, ERCOT, MISO, CAISO)
• Familiarity with trading instruments: DA/RT markets, FTRs, CRRs, PPAs, futures, and swaps
• Knowledge of natural gas, renewables, and carbon markets
• Experience modeling locational marginal prices (LMP), congestion, and portfolio risk
• Understanding of regulatory and compliance data (FERC, EIA, ISO market data)

Machine Learning & AI Expertise

• Experience with supervised, unsupervised, and reinforcement learning for market forecasting or optimization
• Proficient in LLMs (GPT, Llama, Mistral) and RAG (Retrieval-Augmented Generation) pipelines for automating report generation, trade rationale summaries, or market insights
• Hands-on experience fine-tuning or evaluating generative models for quantitative or text-based analytics
• Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI) for autonomous data gathering, analysis, and decision support
• Strong understanding of feature engineering, model interpretability, and bias control

Agentic & Autonomous Decision Systems

• Experience creating intelligent trading assistants or agent frameworks that monitor, forecast, and act based on real-time data
• Familiarity with planning, memory, and multi-agent collaboration concepts
• Implementation of guardrails and ethical constraints in autonomous AI systems

Forecasting & Quantitative Modeling

• Time series modeling (ARIMA, Prophet, LSTM, XGBoost) for price, load, or renewable generation forecasting
• Optimization and scenario modeling for trading positions, hedges, or dispatch strategies
• Proficiency with stochastic modeling, Monte Carlo simulations, and VaR analysis
• Ability to integrate weather data, grid conditions, and market signals into predictive systems

Data Infrastructure & Engineering

• Strong data architecture skills: ETL/ELT pipelines, dbt, Airflow, or Prefect
• Experience with data warehouses (DataBricks, Snowflake)
• Familiarity with vector databases (FAISS, Pinecone, Weaviate) for retrieval-augmented analytics
• Data governance awareness: versioning, lineage, security, and compliance

Analytics, Visualization & Communication

• Strong experience with dashboards and visualization tools (Power BI, Tableau, Plotly)
• Ability to design KPIs and visual analytics for trading performance, market exposure, and forecast accuracy
• Experience building automated insight pipelines or LLM-based analytics assistants
• Skilled in translating technical findings into clear narratives for traders and executives